As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of...As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of navigation resources.Based on the space segment,control segment,and user segment of satellite navigation systems,this paper systematically constructs an offensive-defensive technology system for navigation warfare,and deeply analyzes core measures such as signal enhancement and suppression,autonomous navigation and link jamming,anti-jamming reception,and integrated navigation.It extracts key technologies including adaptive nulling antennas,joint filtering,and multi-dimensional combined jamming,and discusses the technical effectiveness of these technologies by incorporating relevant cases.The advantages of navigation warfare stem from multi-segment coordination and technological inte-gration.In the future,the development directions of navigation warfare will focus on three aspects:enhancing satellite capabilities,tackling core technical challenges,and building a multi-dimensional system.展开更多
The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments ...The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments and accommodates techniques including single-crystal diffraction,powder diffraction,and grazing-incidence wide-angle X-ray scattering(GIWAXS)to enable the characterization of long-range ordered atomic structures.The academic community associated with BL17B engages in research domains encompassing biology,environment,energy,and materials,and a pronounced demand for characterizing short-range ordered structures exists.To address these requirements,BL17B established an advanced X-ray absorption fine structure(XAFS)experimental platform that enabled it to address a wide range of systems,from crystalline to amorphous and from long-range order to short-range order.The XAFS platform allows simultaneous XAFS data acquisition for both the transmission and fluorescence modes within an energy range of 5-23 keV,encompassing the K-edges of titanium to ruthenium and the L3-edges of cesium to bismuth.The platform exemplifies high levels of automation achieved through automated sample assessment and data collection based on large-capacity sample wheels that facilitate remote sample loading.When integrated with a highly integrated control system that simplifies experimental preparation and data collection,the XAFS platform significantly bolsters experimental efficiency and enhances user experience.Notably,the platform boasts an impressively low extended X-ray absorption fine structure(EXAFS)detection limit of 0.04 wt%for dilute copper phthalocyanine(CuPc)samples and an even more remarkable X-ray absorption near edge structure(XANES)detection threshold of 0.01 wt%.These results demonstrate the methodology?s reliability in low-concentration sample analysis,confirming its capability to generate high-quality XAFS data.展开更多
Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation sys...Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation systems face challenges such as high equipment costs,complex operation,bulky size,and insufficient anti-interference performance.To address these limitations,our study developed and validated a novel portable electromagnetic neuronavigation system designed to improve the precision,accessibility,and clinical applicability of electromagnetic navigation technology in cranial surgery.Methods The software and hardware architecture of a portable neural magnetic navigation system was designed.The key technologies of the system were analysed,including electromagnetic positioning algorithms,miniaturized sensor design,optimization of electromagnetic positioning and navigation algorithms,anti-interference signal processing methods,and fast three-dimensional reconstruction algorithms.A prototype was developed,and its accuracy was tested.Finally,a preliminary clinical application evaluation was conducted.Results This study successfully developed a comprehensive portable electromagnetic neuronavigation system capable of achieving preoperative planning,intraoperative real-time positioning and navigation,and postoperative evaluation of navigation outcomes.Through rigorous collaborative testing of the system’s software and hardware,the accuracy of electromagnetic neuronavigation has been validated to meet clinical requirements.Conclusions This study developed a portable neuroelectromagnetic navigation system and validated its effectiveness and safety through rigorous model testing and preliminary clinical applications.The system is characterized by its compact size,high precision,excellent portability,and user-friendly operation,making it highly valuable for promoting navigation technology and advancing the precision and minimally invasive nature of neurosurgical procedures.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigati...Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including at...Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.展开更多
1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become ...1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.展开更多
In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited ...In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.展开更多
This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification metho...This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.展开更多
Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulati...Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulations due to the limitations of experimental methods.To promote the reliable application of machine potentials in high-entropy alloy simulations,first,this work uses NEP models trained on two different datasets to predict the SRO coefficients of NbMoTaW.The results show that within the same machine learning framework,there are significant differences in the prediction of SRO coefficients for the Nb-Nb atomic pair.Subsequently,this work predicts the SRO coefficients of NbMoTaW using the NEP model and the SNAP model,both of which are trained on the same dataset.The results reveal significant discrepancies in SRO predictions for like-element pairs(e.g.,Nb-Nb and W-W)between the two potentials,despite the identical training data.The findings of this study indicate that discrepancies in the prediction results of SRO coefficients can arise from either the same machine learning framework trained on different datasets or different learning frameworks trained on the same dataset.This reflects possible incompleteness in the current training set's coverage of local chemical environments at the atomic scale.Future research should establish unified evaluation standards to assess the capability of training sets to accurately describe complex atomic-scale behaviors such as SRO.展开更多
Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.How...Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.展开更多
In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies an...In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.展开更多
Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant t...Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant tuberculosis(RR-TB)who were hospitalized in the hospital from September 2023 to September 2024 were included.After random equal division,94 patients were included in the control group and received systemic anti-tuberculosis chemotherapy;94 patients were included in the treatment group.Based on systemic anti-tuberculosis treatment,digital subtraction angiography(DSA)technology was used to inject targeted drugs into the bronchial lumen through bronchoscopy to complete anti-tuberculosis treatment.The changes in sputum bacteria and imaging were observed in the two groups.Results:The sputum negative conversion rate in the treatment group was significantly higher than that in the control group(86.2%;70.2%)(u=2.74,P<0.01).The absorption rate of CT imaging lesions(significant absorption)was significantly higher than that of the control group(83.0%;50%)(u=2.45,P<0.05).The closure rate of chest CT cavities was significantly higher than that of the control group(74.2%;39.1%)(u=2.20,P<0.05).During the treatment process,the improvement of clinical symptoms was significantly higher than that of the control group,and the difference was statistically significant.There was no statistically significant difference in the incidence of adverse reactions between the two groups(x^(2)=0.434,P>0.05).Conclusion:Based on DSA,targeted drug infusion within the bronchoscope can significantly improve the efficacy of the disease,with mild adverse reactions that patients can tolerate.It is worthy of promotion and application.展开更多
Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,wh...Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior maps.In order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic goals.At last,comparative experiments were carried out in the real environment.Results show that our method is superior in terms of safety,comfort and docking accuracy.展开更多
Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environ...Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.展开更多
Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to...Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to visualize the optic nerve intraoperatively.To address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this study.The system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical risks.First,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration methods.Additionally,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking accuracy.To evaluate the system’s performance,model experiments were meticulously designed and conducted.The results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)mm.This outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s accuracy.Furthermore,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.展开更多
This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars...This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.展开更多
Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,stru...Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,struggle to cope with complex and dynamic environments.With the development of artificial intelligence,learning-based navigation technology have emerged.Instead of relying on pre-built maps,the agent perceives the environment and make decisions through visual observation,enabling end-to-end navigation.A key challenge is to enhance the generalization ability of the agent in unfamiliar environments.To tackle this challenge,it is necessary to endow the agent with spatial intelligence.Spatial intelligence refers to the ability of the agent to transform visual observations into insights,in-sights into understanding,and understanding into actions.To endow the agent with spatial intelligence,relevant research uses scene graph to represent the environment.We refer to this method as scene graph-based object goal navigation.In this paper,we concentrate on scene graph,offering formal description,computational framework of object goal navigation.We provide a comprehensive summary of the meth-ods for constructing and applying scene graph.Additionally,we present experimental evidence that highlights the critical role of scene graph in improving navigation success.This paper also delineates promising research directions,all aimed at sharpening the focus on scene graph.Overall,this paper shows how scene graph endows the agent with spatial intelligence,aiming to promote the importance of scene graph in the field of intelligent navigation.展开更多
文摘As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of navigation resources.Based on the space segment,control segment,and user segment of satellite navigation systems,this paper systematically constructs an offensive-defensive technology system for navigation warfare,and deeply analyzes core measures such as signal enhancement and suppression,autonomous navigation and link jamming,anti-jamming reception,and integrated navigation.It extracts key technologies including adaptive nulling antennas,joint filtering,and multi-dimensional combined jamming,and discusses the technical effectiveness of these technologies by incorporating relevant cases.The advantages of navigation warfare stem from multi-segment coordination and technological inte-gration.In the future,the development directions of navigation warfare will focus on three aspects:enhancing satellite capabilities,tackling core technical challenges,and building a multi-dimensional system.
基金supported by the Chinese Academy of Science(CAS)Key Technology Talent Program(No.2021000022)。
文摘The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments and accommodates techniques including single-crystal diffraction,powder diffraction,and grazing-incidence wide-angle X-ray scattering(GIWAXS)to enable the characterization of long-range ordered atomic structures.The academic community associated with BL17B engages in research domains encompassing biology,environment,energy,and materials,and a pronounced demand for characterizing short-range ordered structures exists.To address these requirements,BL17B established an advanced X-ray absorption fine structure(XAFS)experimental platform that enabled it to address a wide range of systems,from crystalline to amorphous and from long-range order to short-range order.The XAFS platform allows simultaneous XAFS data acquisition for both the transmission and fluorescence modes within an energy range of 5-23 keV,encompassing the K-edges of titanium to ruthenium and the L3-edges of cesium to bismuth.The platform exemplifies high levels of automation achieved through automated sample assessment and data collection based on large-capacity sample wheels that facilitate remote sample loading.When integrated with a highly integrated control system that simplifies experimental preparation and data collection,the XAFS platform significantly bolsters experimental efficiency and enhances user experience.Notably,the platform boasts an impressively low extended X-ray absorption fine structure(EXAFS)detection limit of 0.04 wt%for dilute copper phthalocyanine(CuPc)samples and an even more remarkable X-ray absorption near edge structure(XANES)detection threshold of 0.01 wt%.These results demonstrate the methodology?s reliability in low-concentration sample analysis,confirming its capability to generate high-quality XAFS data.
基金funded by National Natural Science Foundation of China(No.82272134)Innovative Research Group Project of the National Natural Science Foundation of China(No.82272134,Xiao-lei Chen).
文摘Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation systems face challenges such as high equipment costs,complex operation,bulky size,and insufficient anti-interference performance.To address these limitations,our study developed and validated a novel portable electromagnetic neuronavigation system designed to improve the precision,accessibility,and clinical applicability of electromagnetic navigation technology in cranial surgery.Methods The software and hardware architecture of a portable neural magnetic navigation system was designed.The key technologies of the system were analysed,including electromagnetic positioning algorithms,miniaturized sensor design,optimization of electromagnetic positioning and navigation algorithms,anti-interference signal processing methods,and fast three-dimensional reconstruction algorithms.A prototype was developed,and its accuracy was tested.Finally,a preliminary clinical application evaluation was conducted.Results This study successfully developed a comprehensive portable electromagnetic neuronavigation system capable of achieving preoperative planning,intraoperative real-time positioning and navigation,and postoperative evaluation of navigation outcomes.Through rigorous collaborative testing of the system’s software and hardware,the accuracy of electromagnetic neuronavigation has been validated to meet clinical requirements.Conclusions This study developed a portable neuroelectromagnetic navigation system and validated its effectiveness and safety through rigorous model testing and preliminary clinical applications.The system is characterized by its compact size,high precision,excellent portability,and user-friendly operation,making it highly valuable for promoting navigation technology and advancing the precision and minimally invasive nature of neurosurgical procedures.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金Supported by the National Natural Science Foundation of China(U23A20487)the National Key R&D Program of China(2022YFB3206000)+1 种基金Dr.Li Dak Sum&Yip Yio Chin Development Fund for Regenerative Medicine,Zhejiang Universitythe National Natural Science Foundation of China(61975172).
文摘Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
基金supported by the Basic Science Center Project of the National Natural Science Foundation of China(42388102)the National Natural Science Foundation of China(42174030)+2 种基金the Special Fund of Hubei Luojia Laboratory(220100020)the Major Science and Technology Program for Hubei Province(2022AAA002)the Fundamental Research Funds for the Central Universities of China(2042022dx0001 and 2042023kfyq01)。
文摘Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.
基金supported by the National Level Project of China (No. 2020-JCJQ-ZQ-059)。
文摘1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.
基金supported by the National Natural Science Foundation of China(No.U2037602)。
文摘In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.
基金supported in part by the Doctoral Initiation Fund of Nanchang Hangkong University(No.EA202403107)Jiangxi Province Early Career Youth Science and Technology Talent Training Project(No.CK202403509).
文摘This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.
基金Project supported by the Hunan Provincial Natural Science Foundation(Grant Nos.2024JJ6190 and 2024JK2007-1)。
文摘Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulations due to the limitations of experimental methods.To promote the reliable application of machine potentials in high-entropy alloy simulations,first,this work uses NEP models trained on two different datasets to predict the SRO coefficients of NbMoTaW.The results show that within the same machine learning framework,there are significant differences in the prediction of SRO coefficients for the Nb-Nb atomic pair.Subsequently,this work predicts the SRO coefficients of NbMoTaW using the NEP model and the SNAP model,both of which are trained on the same dataset.The results reveal significant discrepancies in SRO predictions for like-element pairs(e.g.,Nb-Nb and W-W)between the two potentials,despite the identical training data.The findings of this study indicate that discrepancies in the prediction results of SRO coefficients can arise from either the same machine learning framework trained on different datasets or different learning frameworks trained on the same dataset.This reflects possible incompleteness in the current training set's coverage of local chemical environments at the atomic scale.Future research should establish unified evaluation standards to assess the capability of training sets to accurately describe complex atomic-scale behaviors such as SRO.
基金supported by the Foundation of Equipment Preresearch Area(Grant No.80919010303).
文摘Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.
基金co-supported by the National Natural Science Foundation of China(Nos.92371201 and 52192633)the Natural Science Foundation of Shaanxi Province of China(No.2022JC-03)the Aeronautical Science Foundation of China(No.ASFC-20220019070002)。
文摘In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.
基金Science and Education Department Harbin Health Committee Project。
文摘Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant tuberculosis(RR-TB)who were hospitalized in the hospital from September 2023 to September 2024 were included.After random equal division,94 patients were included in the control group and received systemic anti-tuberculosis chemotherapy;94 patients were included in the treatment group.Based on systemic anti-tuberculosis treatment,digital subtraction angiography(DSA)technology was used to inject targeted drugs into the bronchial lumen through bronchoscopy to complete anti-tuberculosis treatment.The changes in sputum bacteria and imaging were observed in the two groups.Results:The sputum negative conversion rate in the treatment group was significantly higher than that in the control group(86.2%;70.2%)(u=2.74,P<0.01).The absorption rate of CT imaging lesions(significant absorption)was significantly higher than that of the control group(83.0%;50%)(u=2.45,P<0.05).The closure rate of chest CT cavities was significantly higher than that of the control group(74.2%;39.1%)(u=2.20,P<0.05).During the treatment process,the improvement of clinical symptoms was significantly higher than that of the control group,and the difference was statistically significant.There was no statistically significant difference in the incidence of adverse reactions between the two groups(x^(2)=0.434,P>0.05).Conclusion:Based on DSA,targeted drug infusion within the bronchoscope can significantly improve the efficacy of the disease,with mild adverse reactions that patients can tolerate.It is worthy of promotion and application.
基金the Technology Project Managed by the State Grid Corporation of China(No.5108-202218280A-2-249-XG)。
文摘Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior maps.In order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic goals.At last,comparative experiments were carried out in the real environment.Results show that our method is superior in terms of safety,comfort and docking accuracy.
基金supported by the Sichuan Science and Technology Program(2025ZNSFSC0005).
文摘Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.
基金the National Natural Science Foundation of China(Nos.82330063 and M-0019)the Interdisciplinary Program of Shanghai Jiao Tong University(Nos.YG2022QN056,YG2023ZD19,and YG2023ZD15)+2 种基金the Cross Disciplinary Research Fund of Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of Medicine(No.JYJC202115)the Translation Clinical R&D Project of Medical Robot of Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University School of Medicine(No.IMR-NPH202002)the Shanghai Key Clinical Specialty,Shanghai Eye Disease Research Center(No.2022ZZ01003)。
文摘Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy.However,a major challenge faced during the procedure is the inability to visualize the optic nerve intraoperatively.To address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this study.The system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical risks.First,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration methods.Additionally,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking accuracy.To evaluate the system’s performance,model experiments were meticulously designed and conducted.The results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)mm.This outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s accuracy.Furthermore,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.
基金supported by the National Key Research and Development Program of China(2022YFA1004703)the National Natural Science Foundation of China(62088101).
文摘This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.
基金Supported by the Major Science and Technology Project of Hubei Province of China(2022AAA009)the Open Fund of Hubei Luojia Laboratory。
文摘Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,struggle to cope with complex and dynamic environments.With the development of artificial intelligence,learning-based navigation technology have emerged.Instead of relying on pre-built maps,the agent perceives the environment and make decisions through visual observation,enabling end-to-end navigation.A key challenge is to enhance the generalization ability of the agent in unfamiliar environments.To tackle this challenge,it is necessary to endow the agent with spatial intelligence.Spatial intelligence refers to the ability of the agent to transform visual observations into insights,in-sights into understanding,and understanding into actions.To endow the agent with spatial intelligence,relevant research uses scene graph to represent the environment.We refer to this method as scene graph-based object goal navigation.In this paper,we concentrate on scene graph,offering formal description,computational framework of object goal navigation.We provide a comprehensive summary of the meth-ods for constructing and applying scene graph.Additionally,we present experimental evidence that highlights the critical role of scene graph in improving navigation success.This paper also delineates promising research directions,all aimed at sharpening the focus on scene graph.Overall,this paper shows how scene graph endows the agent with spatial intelligence,aiming to promote the importance of scene graph in the field of intelligent navigation.
