A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency a...A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.展开更多
Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigat...Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigation satellite systems(GNSSs)have been a valuable tool in monitoring seismic motions,allowing permanent displacement computation to be unambiguously achieved.As a valuable tool presented to the seismic commu nity,the GSeisRT software developed by Wuhan University(China)can realize multi-GNSS precise point positioning with ambiguity resolution(PPP-AR)and achieve centimeterlevel to sub-centimeter-level precision in real time.While the stable maintenance of a global precise point positioning(PPP)service is challenging,this software is capable of estimating satellite clocks and phase biases in real time using a regional GNSS network.This capability makes GSeisRT especially suitable for proprietary GNSS networks and,more importantly,the highest possible positio ning precision and reliability can be obtained.According to real-time results from the Network of the Americas,the mean root mean square(RMS)errors of kinematic PPP-AR over a 24 h span are as low as 1.2,1.3,and 3.0 cm in the east,north,and up components,respectively.Within the few minutes that span a typical seismic event,a horizontal displacement precision of 4 mm can be achieved.The positioning precision of the GSeisRT regional PPP/PPP-AR is 30%-40%higher than that of the global PPP/PPP-AR.Since 2019,GSeisRT has successfully recorded the static,dynamic,and peak ground displacements for the 2020Oaxaca,Mexico moment magnitude(Mw)7.4 event;the 2020 Lone Pine,California Mw 5.8 event;and the 2021 Qinghai,China Mw 7.3 event in real time.The resulting immediate magnitude estimates have an error of around 0.1 only.The GSeisRT software is open to the scientific community and has been applied by the China Earthquake Ne tworks Center,the EarthScope Consortium of the United States,the National Seismological Center of Chile,Institute of Geological and Nuclear Sciences Limited(GNS Science Te PūAo)of New Zealand,and the Geospatial Information Agency of Indonesia.展开更多
For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Veh...For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.展开更多
The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave...The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave infrared wavelengths as beacon light can reduce atmospheric absorption and signal attenuation.However,there are strong non-uniformity and blind pixels in the short-wave infrared image,which makes the image distorted and leads to the decrease of spot centroid positioning accuracy.Therefore,the high-precision localization of the spot centroid of the short-wave infrared images is of great research significance.A high-precision spot centroid positioning model for short-wave infrared is proposed to correct for non-uniformity and blind pixels in short-wave infrared images and quantify the localization errors caused by the two,further model-based localization error simulations are performed,and a novel spot centroid positioning payload for satellite laser communications has been designed using the latest 640×512 planar array InGaAs shortwave infrared detector.The experimental results show that the non-uniformity of the corrected image is reduced from 7%to 0.6%,the blind pixels rejection rate reaches 100%,the frame rate can be up to 2000 Hz,and the spot centroid localization accuracy is as high as 0.1 pixel point,which realizes high-precision spot centroid localization of high-frame-frequency short-wave infrared images.展开更多
Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. Thi...Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.展开更多
The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)den...The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.展开更多
In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based po...In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.展开更多
Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in...Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in complex signal environments with multipath interference and non-line-of-sight(NLOS)conditions.Reconfigurable intelligent surfaces(RIS),an innovative technology that can flexibly control signal propagation,offer new possibilities for positioning systems.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning...Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.展开更多
As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dyna...As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning(DP)systems such as Wind Turbine Installation Vessels(WTIVs)and Service Operation Vessels(SOVs).Despite their importance,long-term demand forecasting for such vessels remains underexplored,especially in South Korea.This study presents the dDP-W model,a System Dynamics(SD)-based framework that simulates the evolving demand for DP vessels under varying technological,policy,and environmental conditions.Unlike conventional methods based on historical extrapolation,the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap(2026-2036).Three WTIV demand scenarios—baseline,optimistic,and pessimistic—were constructed based on vessel productivity and weather-related downtime.SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios.The simulations indicate that WTIV demand peaks in the early 2030s,requiring 6 to 7 vessels depending on conditions,while SOV demand increases steadily,reaching nearly 70 vessels by 2036.These findings highlight the need for early vessel procurement,infrastructure investment,and workforce preparation.By integrating technical,logistical,and policy factors into a dynamic model,this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy.The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals.展开更多
Aiming at the terminal defense problem of aircraft,this paper proposes a method to simultaneously achieve terminal defense and seize the dominant position.The method employs aλ-return based reinforcement learning alg...Aiming at the terminal defense problem of aircraft,this paper proposes a method to simultaneously achieve terminal defense and seize the dominant position.The method employs aλ-return based reinforcement learning algorithm,which can be applied to the flight assistance decision-making system to improve the pilot’s survivability.First,we model the environment to simulate the interaction between air-to-air missiles and aircraft.Subsequently,we propose aλ-return based approach to improve the deep Q learning network(DQN),deep advantageous actor criticism(A2C),and proximity policy optimization(PPO)algorithms used to train manoeuvre strategies.The method employs an action space containing nine manoeuvres and defines the off-target distance at the end of the scene as a sparse reward for algorithm training.Simulation results show that the convergence speed of the three improved algorithms is significantly improved when using theλ-return method.Moreover,the effect of the fetch value on the convergence speed is verified by ablation experiments.In order to solve the illegal behavior problem in the training process,we also design a backtracking-based illegal behavior masking mechanism,which improves the data generation efficiency of the environment model and promotes effective algorithm training.展开更多
Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rat...Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rate among invertebrates. This biological phenomenon contrasts sharply with engineered systems, which generally associates high accuracy with substantial energy consumption. Inspired by the Scorpion Compound Slit Sensilla (SCSS) with a stress field modulation strategy, a bionic positioning sensor with superior precision and minimal power consumption is developed for the first time, which utilizes the particular Minimum Positioning Units (MPUs) to efficiently locate vibration signals. The single MPU of the SCSS can recognize the direction of collinear loads by regulating the stress field distribution and further, the coupling action of three MPUs can realize all-angle vibration monitoring in plane. Experiments demonstrate that the bionic positioning sensor achieves 1.43 degrees of angle-error-free accuracy without additional energy supply. As a proof of concept, two bionic positioning sensors and machine learning algorithm are integrated to provide centimeter (cm)-accuracy target localization, ideally suited for the man-machine interaction. The novel design offers a new mechanism for the design of traditional positioning devices, improving precision and efficiency in both the meta-universe and real-world Internet-connected systems.展开更多
The spatiotemporal variations of sound speed, particularly the drastic variation in depth, significantly affect seafloor geodetic positioning precision. For this reason, the global navigation satellite system-acoustic...The spatiotemporal variations of sound speed, particularly the drastic variation in depth, significantly affect seafloor geodetic positioning precision. For this reason, the global navigation satellite system-acoustic(GNSS-A) positioning technology typically uses in-situ sound speed profiles(SSPs) and considers the impact of these variations at the data post-processing stage. However, in-situ SSP measurement is costly and somewhat hinders the timeliness of seafloor geodetic monitoring. We generalize the bilinear SSP(BL-SSP) to be a piecewise-linear SSP, whose model parameters are estimated from GNSS-A observations. In addition, we construct a set of constraints based on a priori marine environment observation to stabilize SSP inversion and propose an algorithm to recursively conduct the inversion, e.g.,the trilinear SSP(TL-SSP) inversion is initialized using the BL-SSP inversion result. The proposed model is verified by long-term GNSS-A seafloor geodetic observations. It shows that the root mean square error(RMSE) of the TL-SSP inversion result is 10.87 m/s, compared to 11.08 m/s for the traditional BL-SSP, with significant improvements observed in shallow and middle water layers. Furthermore, when replacing the in-situ SSP with the inverted SSP for precise seafloor geodetic positioning and incorporating the acoustic delay parameters, the TL-SSP-based positioning demonstrates higher accuracy than the BL-SSP-based approach. Relative to the positioning result based on the in-situ SSP, the mean bias, standard deviation and RMSE of the horizontal positioning error are better than 0.003 m, 0.005 m,and 0.006 m, respectively, while those of the vertical positioning error are better than 0.03 m, 0.04 m, and 0.04 m,respectively. Compared with BL-SSP, TL-SSP can achieve a positioning error reduction along the E-direction, Ndirection, and U-direction by 16.7%, 15.0%, and 5.5%, respectively.展开更多
Visual indoor positioning methods have the potential for widespread application in complex large-scale indoor environments,such as shopping centers and hospitals.However,during the visual positioning process,passing p...Visual indoor positioning methods have the potential for widespread application in complex large-scale indoor environments,such as shopping centers and hospitals.However,during the visual positioning process,passing pedestrians may cause occlusion in the visual image,leading to large deviations in the visual positioning results.Aiming at the problem of feature occlusion in visual images caused by pedestrians,this paper proposes a visual indoor positioning system that combines semantic segmentation and image restoration.The paper proposes a method called the fast image segmentation repair(FISR),which segments and rapidly repairs the selected image to eliminate the influence of pedestrians on image feature extraction and improve positioning accuracy.In addition,the paper proposes a method called local feature based bag-of-visual-words combined with high-level semantic information(LFHS)for image retrieval.LFHS uses both local features and high-level semantic information to obtain more comprehensive and accurate representations of image features.This approach improves the accuracy and robustness of image retrieval by harnessing the combined power of local features and high-level semantic information.Experimental results show that the proposed positioning method reduces the average positioning error by 0.35 m compared with NetVLAD and 0.49 m compared with MixVPR,significantly improving the performance of visual positioning technology.展开更多
This study aimed to explore an effective nursing plan for peripherally inserted central catheter(PICC)placement guided by endocardial electrocardiogram(ECG)positioning technology and to analyze related nursing problem...This study aimed to explore an effective nursing plan for peripherally inserted central catheter(PICC)placement guided by endocardial electrocardiogram(ECG)positioning technology and to analyze related nursing problems and countermeasures.A total of 96 patients who underwent PICC placement using ECG-guided positioning technology in our hospital from January 2024 to December 2024 were selected and randomly divided into an experimental group(n=48)and a control group(n=48)using a random number table.The control group received routine basic nursing care,while the experimental group was provided with comprehensive high-quality nursing care.The results showed that the success rate of one-time catheter placement was significantly higher in the experimental group than in the control group(P<0.05),while the incidence of complications was notably lower in the experimental group(P<0.05).These findings suggest that comprehensive high-quality nursing care during PICC placement guided by ECG positioning technology can effectively enhance the success rate of catheter placement and reduce complications,indicating that this nursing approach is valuable for clinical promotion and application.展开更多
Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particular...Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particularly in turnout sections.To address these challenges,a fuzzy boundary guidance and oriented Gaussian function-based anchor-free network termed the rail positioning network(RP-Net)is proposed for rail positioning in turnout sections.First,an oriented Gaussian function-based label generation strategy is introduced.This strategy produces smoother and more accu-rate label values by accounting for the specific aspect ratios and orientations of the rails.Second,a fuzzy boundary learning module is developed to enhance the network’s abil-ity to model the rail boundary regions effectively.Further-more,a boundary guidance module is developed to direct the network in fusing the features obtained from the downs-ampled network output with the boundary region features,which have been enhanced to contain more refined posi-tional and structural information.A local channel attention mechanism is integrated into this module to identify critical channels.Finally,experiments conducted on the tracking dataset show that the proposed RP-Net achieves high posi-tioning accuracy and demonstrates strong adaptability in complex scenarios.展开更多
The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor env...The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.展开更多
Total hip arthroplasty(THA)has limitations in grinding angles,prosthesis placements,and thickness variations.THA robotics offer promise but encounter challenges like manual control of the robotic arm for precise posit...Total hip arthroplasty(THA)has limitations in grinding angles,prosthesis placements,and thickness variations.THA robotics offer promise but encounter challenges like manual control of the robotic arm for precise positioning and potential over-grinding when controlled manually.This paper presents a THA surgical robot system with automatic positioning and automatic grinding and filing functions.It achieves precise positioning during the surgery by using the singular value decomposition of initial value screening and sliding mode control(SMC),and ensures uniformity,stability and controlled filing thickness through the designed end grinding and filing actuator system.It has been verified experimentally that the average position errors in the x,y,and z directions are 0.692 mm,0.512 mm,and 0.66 mm respectively,and the Euclidean distance error is 1.322 mm.The average angle error is less than 1.136°.The end effector can perform automatic grinding according to the predetermined planning value within the safe force threshold of 30 N.This THA surgical robot system can meet the requirements of the hip replacement surgery for the accuracy,driving ability and robustness of the system.展开更多
Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The gr...Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.展开更多
基金National Natural Science Foundation of China(No.12472038)Natural Science Foundation of Jiangsu Province(No.BK20230688)+2 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.22KJB440004)Key Research and Development Program of Xuzhou(No.KC22404)Research Fund for Doctoral Degree Teachers of Jiangsu Normal University of China(No.22XFRS011).
文摘A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.
基金funded by National Science Foundation of China(42025401)National Key Research and Development Program of China(2022YFB3903800)。
文摘Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigation satellite systems(GNSSs)have been a valuable tool in monitoring seismic motions,allowing permanent displacement computation to be unambiguously achieved.As a valuable tool presented to the seismic commu nity,the GSeisRT software developed by Wuhan University(China)can realize multi-GNSS precise point positioning with ambiguity resolution(PPP-AR)and achieve centimeterlevel to sub-centimeter-level precision in real time.While the stable maintenance of a global precise point positioning(PPP)service is challenging,this software is capable of estimating satellite clocks and phase biases in real time using a regional GNSS network.This capability makes GSeisRT especially suitable for proprietary GNSS networks and,more importantly,the highest possible positio ning precision and reliability can be obtained.According to real-time results from the Network of the Americas,the mean root mean square(RMS)errors of kinematic PPP-AR over a 24 h span are as low as 1.2,1.3,and 3.0 cm in the east,north,and up components,respectively.Within the few minutes that span a typical seismic event,a horizontal displacement precision of 4 mm can be achieved.The positioning precision of the GSeisRT regional PPP/PPP-AR is 30%-40%higher than that of the global PPP/PPP-AR.Since 2019,GSeisRT has successfully recorded the static,dynamic,and peak ground displacements for the 2020Oaxaca,Mexico moment magnitude(Mw)7.4 event;the 2020 Lone Pine,California Mw 5.8 event;and the 2021 Qinghai,China Mw 7.3 event in real time.The resulting immediate magnitude estimates have an error of around 0.1 only.The GSeisRT software is open to the scientific community and has been applied by the China Earthquake Ne tworks Center,the EarthScope Consortium of the United States,the National Seismological Center of Chile,Institute of Geological and Nuclear Sciences Limited(GNS Science Te PūAo)of New Zealand,and the Geospatial Information Agency of Indonesia.
基金supported by the National Natural Science Foundation of China(No.62271399)the National Key Research and Development Program of China(No.2022YFB1807102)。
文摘For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.
基金Supported by the Short-wave Infrared Camera Systems(B025F40622024)。
文摘The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave infrared wavelengths as beacon light can reduce atmospheric absorption and signal attenuation.However,there are strong non-uniformity and blind pixels in the short-wave infrared image,which makes the image distorted and leads to the decrease of spot centroid positioning accuracy.Therefore,the high-precision localization of the spot centroid of the short-wave infrared images is of great research significance.A high-precision spot centroid positioning model for short-wave infrared is proposed to correct for non-uniformity and blind pixels in short-wave infrared images and quantify the localization errors caused by the two,further model-based localization error simulations are performed,and a novel spot centroid positioning payload for satellite laser communications has been designed using the latest 640×512 planar array InGaAs shortwave infrared detector.The experimental results show that the non-uniformity of the corrected image is reduced from 7%to 0.6%,the blind pixels rejection rate reaches 100%,the frame rate can be up to 2000 Hz,and the spot centroid localization accuracy is as high as 0.1 pixel point,which realizes high-precision spot centroid localization of high-frame-frequency short-wave infrared images.
文摘Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.
基金supported in part by the National Natural Science Foundation of China(Nos.62171375,62271397,62001392,62101458,62173276,61803310 and 61801394)the Shenzhen Science and Technology Innovation ProgramChina(No.JCYJ20220530161615033)。
文摘The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.
基金Project(52272339)supported by the National Natural Science Foundation of ChinaProject(2023YFB390730303)supported by the National Key Research and Development Program of China+2 种基金Project(L2023G004)supported by the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.Project(QZKFKT2023-005)supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive,ChinaProject(2022JZZ05)supported by the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway(Central South University),China。
文摘In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.
基金supported by the Open Fund Project of Key Laboratory of Ocean Observation Technology,MNR(2023klootA01).
文摘Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in complex signal environments with multipath interference and non-line-of-sight(NLOS)conditions.Reconfigurable intelligent surfaces(RIS),an innovative technology that can flexibly control signal propagation,offer new possibilities for positioning systems.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
基金supported by the National Key Research and Development Program of China(2023YFB3907300)the Fundamental Research Funds for the Central Universities(2024JBMC002)the National Natural Science Foundation of China(T2222015,U2268206).
文摘Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.
文摘As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning(DP)systems such as Wind Turbine Installation Vessels(WTIVs)and Service Operation Vessels(SOVs).Despite their importance,long-term demand forecasting for such vessels remains underexplored,especially in South Korea.This study presents the dDP-W model,a System Dynamics(SD)-based framework that simulates the evolving demand for DP vessels under varying technological,policy,and environmental conditions.Unlike conventional methods based on historical extrapolation,the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap(2026-2036).Three WTIV demand scenarios—baseline,optimistic,and pessimistic—were constructed based on vessel productivity and weather-related downtime.SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios.The simulations indicate that WTIV demand peaks in the early 2030s,requiring 6 to 7 vessels depending on conditions,while SOV demand increases steadily,reaching nearly 70 vessels by 2036.These findings highlight the need for early vessel procurement,infrastructure investment,and workforce preparation.By integrating technical,logistical,and policy factors into a dynamic model,this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy.The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals.
文摘Aiming at the terminal defense problem of aircraft,this paper proposes a method to simultaneously achieve terminal defense and seize the dominant position.The method employs aλ-return based reinforcement learning algorithm,which can be applied to the flight assistance decision-making system to improve the pilot’s survivability.First,we model the environment to simulate the interaction between air-to-air missiles and aircraft.Subsequently,we propose aλ-return based approach to improve the deep Q learning network(DQN),deep advantageous actor criticism(A2C),and proximity policy optimization(PPO)algorithms used to train manoeuvre strategies.The method employs an action space containing nine manoeuvres and defines the off-target distance at the end of the scene as a sparse reward for algorithm training.Simulation results show that the convergence speed of the three improved algorithms is significantly improved when using theλ-return method.Moreover,the effect of the fetch value on the convergence speed is verified by ablation experiments.In order to solve the illegal behavior problem in the training process,we also design a backtracking-based illegal behavior masking mechanism,which improves the data generation efficiency of the environment model and promotes effective algorithm training.
基金supported by the National Natural Science Foundation of China(No.52175269)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.52021003)+2 种基金Science and Technology Research Project of Education Department of Jilin Province(JJKH20231146KJ,JJKH20241262KJ)Project ZR2024ME104 supported by Shandong Provincial Natural Science FoundationChina Postdoctoral Science Foundation(No.2024M751086).
文摘Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rate among invertebrates. This biological phenomenon contrasts sharply with engineered systems, which generally associates high accuracy with substantial energy consumption. Inspired by the Scorpion Compound Slit Sensilla (SCSS) with a stress field modulation strategy, a bionic positioning sensor with superior precision and minimal power consumption is developed for the first time, which utilizes the particular Minimum Positioning Units (MPUs) to efficiently locate vibration signals. The single MPU of the SCSS can recognize the direction of collinear loads by regulating the stress field distribution and further, the coupling action of three MPUs can realize all-angle vibration monitoring in plane. Experiments demonstrate that the bionic positioning sensor achieves 1.43 degrees of angle-error-free accuracy without additional energy supply. As a proof of concept, two bionic positioning sensors and machine learning algorithm are integrated to provide centimeter (cm)-accuracy target localization, ideally suited for the man-machine interaction. The novel design offers a new mechanism for the design of traditional positioning devices, improving precision and efficiency in both the meta-universe and real-world Internet-connected systems.
基金The National Key Research and Development Program under contract No. 2024YFB3909702the National Natural Science Foundation of China under contract Nos 42474014, 41931076, and 42388102+2 种基金the Scientific and Technology Inmo-vation Program of Laoshan Laboratory under contract Nos LSKJ202205100 and LSKJ202205105the Independent Research Project of State Key Laboratory of Geo-information Engineering under contract SKLGIE2023-ZZ-8the Scientific Research Project of Chinese Academy of Surveying and Mapping under contract No. AR2501。
文摘The spatiotemporal variations of sound speed, particularly the drastic variation in depth, significantly affect seafloor geodetic positioning precision. For this reason, the global navigation satellite system-acoustic(GNSS-A) positioning technology typically uses in-situ sound speed profiles(SSPs) and considers the impact of these variations at the data post-processing stage. However, in-situ SSP measurement is costly and somewhat hinders the timeliness of seafloor geodetic monitoring. We generalize the bilinear SSP(BL-SSP) to be a piecewise-linear SSP, whose model parameters are estimated from GNSS-A observations. In addition, we construct a set of constraints based on a priori marine environment observation to stabilize SSP inversion and propose an algorithm to recursively conduct the inversion, e.g.,the trilinear SSP(TL-SSP) inversion is initialized using the BL-SSP inversion result. The proposed model is verified by long-term GNSS-A seafloor geodetic observations. It shows that the root mean square error(RMSE) of the TL-SSP inversion result is 10.87 m/s, compared to 11.08 m/s for the traditional BL-SSP, with significant improvements observed in shallow and middle water layers. Furthermore, when replacing the in-situ SSP with the inverted SSP for precise seafloor geodetic positioning and incorporating the acoustic delay parameters, the TL-SSP-based positioning demonstrates higher accuracy than the BL-SSP-based approach. Relative to the positioning result based on the in-situ SSP, the mean bias, standard deviation and RMSE of the horizontal positioning error are better than 0.003 m, 0.005 m,and 0.006 m, respectively, while those of the vertical positioning error are better than 0.03 m, 0.04 m, and 0.04 m,respectively. Compared with BL-SSP, TL-SSP can achieve a positioning error reduction along the E-direction, Ndirection, and U-direction by 16.7%, 15.0%, and 5.5%, respectively.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+2 种基金the Open Research Fund of National Mobile Communications Research Laboratory Southeast University(No.2023D07)the Outstanding Youth Program of Natural Science Foundation of Heilongjiang Province(No.YQ2020F012)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘Visual indoor positioning methods have the potential for widespread application in complex large-scale indoor environments,such as shopping centers and hospitals.However,during the visual positioning process,passing pedestrians may cause occlusion in the visual image,leading to large deviations in the visual positioning results.Aiming at the problem of feature occlusion in visual images caused by pedestrians,this paper proposes a visual indoor positioning system that combines semantic segmentation and image restoration.The paper proposes a method called the fast image segmentation repair(FISR),which segments and rapidly repairs the selected image to eliminate the influence of pedestrians on image feature extraction and improve positioning accuracy.In addition,the paper proposes a method called local feature based bag-of-visual-words combined with high-level semantic information(LFHS)for image retrieval.LFHS uses both local features and high-level semantic information to obtain more comprehensive and accurate representations of image features.This approach improves the accuracy and robustness of image retrieval by harnessing the combined power of local features and high-level semantic information.Experimental results show that the proposed positioning method reduces the average positioning error by 0.35 m compared with NetVLAD and 0.49 m compared with MixVPR,significantly improving the performance of visual positioning technology.
文摘This study aimed to explore an effective nursing plan for peripherally inserted central catheter(PICC)placement guided by endocardial electrocardiogram(ECG)positioning technology and to analyze related nursing problems and countermeasures.A total of 96 patients who underwent PICC placement using ECG-guided positioning technology in our hospital from January 2024 to December 2024 were selected and randomly divided into an experimental group(n=48)and a control group(n=48)using a random number table.The control group received routine basic nursing care,while the experimental group was provided with comprehensive high-quality nursing care.The results showed that the success rate of one-time catheter placement was significantly higher in the experimental group than in the control group(P<0.05),while the incidence of complications was notably lower in the experimental group(P<0.05).These findings suggest that comprehensive high-quality nursing care during PICC placement guided by ECG positioning technology can effectively enhance the success rate of catheter placement and reduce complications,indicating that this nursing approach is valuable for clinical promotion and application.
基金Major Scientific Research Projects of China Railway Group(No.K2019G046)the National Key Research and Devel-opment Program of China(No.2020YFB1600700).
文摘Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particularly in turnout sections.To address these challenges,a fuzzy boundary guidance and oriented Gaussian function-based anchor-free network termed the rail positioning network(RP-Net)is proposed for rail positioning in turnout sections.First,an oriented Gaussian function-based label generation strategy is introduced.This strategy produces smoother and more accu-rate label values by accounting for the specific aspect ratios and orientations of the rails.Second,a fuzzy boundary learning module is developed to enhance the network’s abil-ity to model the rail boundary regions effectively.Further-more,a boundary guidance module is developed to direct the network in fusing the features obtained from the downs-ampled network output with the boundary region features,which have been enhanced to contain more refined posi-tional and structural information.A local channel attention mechanism is integrated into this module to identify critical channels.Finally,experiments conducted on the tracking dataset show that the proposed RP-Net achieves high posi-tioning accuracy and demonstrates strong adaptability in complex scenarios.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+1 种基金the Open Research Fund of National Mobile Communications Research Laboratory in Southeast University(No.2023D07)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.
基金supported by the Li Ka Shing Foundation Cross Research Project(No.2020LKSFG02D)the Guangdong Basic and Applied Basic Research Foundation(Nos.2021A1515011285,2022A1515110566,2023A151501221574 and 2019A1515010800)+2 种基金Major Project under the Science and Technology Development Scheme of Guangdong Province(Nos.210715106900918 and[2020]53-129)the Shantou Science and Technology Plan Medical and Health Category Project(No.211114216492935)the 2022 Guangdong Science and Technology Innovation Strategy Special Fund for University Students(Science and Technology Innovation Cultivation)Project(No.pdjh2022a0186).
文摘Total hip arthroplasty(THA)has limitations in grinding angles,prosthesis placements,and thickness variations.THA robotics offer promise but encounter challenges like manual control of the robotic arm for precise positioning and potential over-grinding when controlled manually.This paper presents a THA surgical robot system with automatic positioning and automatic grinding and filing functions.It achieves precise positioning during the surgery by using the singular value decomposition of initial value screening and sliding mode control(SMC),and ensures uniformity,stability and controlled filing thickness through the designed end grinding and filing actuator system.It has been verified experimentally that the average position errors in the x,y,and z directions are 0.692 mm,0.512 mm,and 0.66 mm respectively,and the Euclidean distance error is 1.322 mm.The average angle error is less than 1.136°.The end effector can perform automatic grinding according to the predetermined planning value within the safe force threshold of 30 N.This THA surgical robot system can meet the requirements of the hip replacement surgery for the accuracy,driving ability and robustness of the system.
基金the National Key Research and Development Program of China(2023YFB3907300)the National Natural Science Foundation of China(U2268206,T2222015)the Beijing Natural Science Foundation(4232031).
文摘Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.
