The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navig...The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navigation was the focus of the doctoral thesis written by the author,the 29th and last PhD thesis supervised by Prof.Ackermann.The International Master’s Program Photogrammetry and Geoinformatics,which the author established with colleagues at Stuttgart University of Applied Sciences(HfT Stuttgart)in 1999,was a consequence of Prof.Ackermann’s benevolent promotion of international knowledge transfer in teaching.Both topics are reflected in this article;they provide further splashes of color in Prof.Ackermann’s oeuvre.展开更多
Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark...Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.展开更多
BACKGROUND Medical robot is a promising surgical tool,but no specific one has been designed for interventional treatment of chronic pain.We developed a computed tomography-image based navigation robot using a new regi...BACKGROUND Medical robot is a promising surgical tool,but no specific one has been designed for interventional treatment of chronic pain.We developed a computed tomography-image based navigation robot using a new registration method with binocular vision.This kind of robot is appropriate for minimal invasive interventional procedures and easy to operate.The feasibility,accuracy and stability of this new robot need to be tested.AIM To assess quantitatively the feasibility,accuracy and stability of the binocularstereo-vision-based navigation robot for minimally invasive interventional procedures.METHODS A box model was designed for assessing the accuracy for targets at different distances.Nine(three sets)lead spheres were embedded in the model as puncture goals.The entry-to-target distances were set 50 mm(short-distance),100 mm(medium-distance)and 150 mm(long-distance).Puncture procedure was repeated three times for each goal.The Euclidian error of each puncture was calculated and statistically analyzed.Three head phantoms were used to explore the clinical feasibility and stability.Three independent operators conducted foramen ovale placement on head phantoms(both sides)by freehand or under the guidance of robot(18 punctures with each method).The operation time,adjustment time and one-time success rate were recorded,and the two guidancemethods were compared.RESULTS On the box model,the mean puncture errors of navigation robot were 1.7±0.9 mm for the short-distance target,2.4±1.0 mm for the moderate target and 4.4±1.4 mm for the long-distance target.On the head phantom,no obvious differences in operation time and adjustment time were found among the three performers(P>0.05).The median adjustment time was significantly less under the guidance of the robot than under free hand.The one-time success rate was significantly higher with the robot(P<0.05).There was no obvious difference in operation time between the two methods(P>0.05).CONCLUSION In the laboratory environment,accuracy of binocular-stereo-vision-based navigation robot is acceptable for target at 100 mm depth or less.Compared with freehand,foramen ovale placement accuracy can be improved with robot guidance.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
The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinf...The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinforcement signal into an evolutionary algorithm.The reinforcement signal is calculated by estimating the optical flow densities in areas of the camera to determine whether they are“dense”or“thin”which has a relationship with the proximity of objects.The results obtained show that the present approach improves the rate of learning compared with a method with a simple reward system and without the evolutionary component.The proposed system was implemented in a virtual robotics system using the CoppeliaSim software and in communication with Python.展开更多
A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative ...A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative position,velocity and attitude of two unmanned aerial vehicles (UAVs).The second-order divided difference filter which makes use of multidimensional interpolation formulations to approximate the nonlinear transformations could achieve more accurate estimation and faster convergence from inaccurate initial conditions than standard extended Kalman filter.The filter formulation is based on relative motion equations.The global attitude parameterization is given by quarternion,while a generalized three-dimensional attitude representation is used to define the local attitude error.Simulation results are shown to compare the performance of the second-order divided difference filter with a standard extended Kalman filter approach.展开更多
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
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
The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vi...The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.展开更多
Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in c...Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in complex environments.To address this problem,we have developed a permanent-magnet-actuated microswarm navigation system to achieve precise control of micro/nanorobots in complex fluid environments.The controlled microswarm is composed of monodisperse Fe_(3)O_(4)@PVP nanoclusters synthesized using the polyol method.These nanoclusters can self-assemble into highly controllable microswarm structures under a rotating magnetic field and are then guided by the robotic system for precise navigation.The system uses visual positioning and motion control to enable real-time dynamic navigation.In experiments,it successfully performed autonomous navigation over a 55 mm distance in a transparent channel,with flow rates ranging from 0 to 10 mm/s.It completed the task in 132 s at an average speed of over 0.45 mm/s,with an average trajectory tracking error of only 0.28 mm.These results demonstrate excellent path accuracy and stability under various flow rate conditions,validating the system’s adaptability and efficiency in fluid environments and highlighting its potential for biomedical applications.This study offers a robust and versatile platform for expanding micro/nanorobot applications in biomedicine.展开更多
In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile...In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile sensing ability.In recent years,vision-based tactile sensing technology has been the research hotspot and frontier in the field of tactile perception.Compared to conventional tactile sensing technologies,vision-based tactile sensing technologies are capable of obtaining highquality and high-resolution tactile information at a lower cost,while not being limited by the size and shape of sensors.Several previous articles have reviewed the sensing mechanism and electrical components of vision-based sensors,greatly promoting the innovation of tactile sensing.Different from existing reviews,this article concentrates on the underlying tracking method which converts real-time images into deformation information,including contact,sliding and friction.We will show the history and development of both model-based and model-free tracking methods,among which model-based approaches rely on schematic mechanical theories,and model-free approaches mainly involve machine learning algorithms.Comparing the efficiency and accuracy of existing deformation tracking methods,future research directions of vision-based tactile sensors for smart manipulations and robots are also discussed.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
文摘The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navigation was the focus of the doctoral thesis written by the author,the 29th and last PhD thesis supervised by Prof.Ackermann.The International Master’s Program Photogrammetry and Geoinformatics,which the author established with colleagues at Stuttgart University of Applied Sciences(HfT Stuttgart)in 1999,was a consequence of Prof.Ackermann’s benevolent promotion of international knowledge transfer in teaching.Both topics are reflected in this article;they provide further splashes of color in Prof.Ackermann’s oeuvre.
基金supported by National Basic Research Program of China (No.2010CB731800)
文摘Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.
基金Supported by Jiangsu Provincial Department of Science and Technology,No.BE2017603 and No.BE2017675。
文摘BACKGROUND Medical robot is a promising surgical tool,but no specific one has been designed for interventional treatment of chronic pain.We developed a computed tomography-image based navigation robot using a new registration method with binocular vision.This kind of robot is appropriate for minimal invasive interventional procedures and easy to operate.The feasibility,accuracy and stability of this new robot need to be tested.AIM To assess quantitatively the feasibility,accuracy and stability of the binocularstereo-vision-based navigation robot for minimally invasive interventional procedures.METHODS A box model was designed for assessing the accuracy for targets at different distances.Nine(three sets)lead spheres were embedded in the model as puncture goals.The entry-to-target distances were set 50 mm(short-distance),100 mm(medium-distance)and 150 mm(long-distance).Puncture procedure was repeated three times for each goal.The Euclidian error of each puncture was calculated and statistically analyzed.Three head phantoms were used to explore the clinical feasibility and stability.Three independent operators conducted foramen ovale placement on head phantoms(both sides)by freehand or under the guidance of robot(18 punctures with each method).The operation time,adjustment time and one-time success rate were recorded,and the two guidancemethods were compared.RESULTS On the box model,the mean puncture errors of navigation robot were 1.7±0.9 mm for the short-distance target,2.4±1.0 mm for the moderate target and 4.4±1.4 mm for the long-distance target.On the head phantom,no obvious differences in operation time and adjustment time were found among the three performers(P>0.05).The median adjustment time was significantly less under the guidance of the robot than under free hand.The one-time success rate was significantly higher with the robot(P<0.05).There was no obvious difference in operation time between the two methods(P>0.05).CONCLUSION In the laboratory environment,accuracy of binocular-stereo-vision-based navigation robot is acceptable for target at 100 mm depth or less.Compared with freehand,foramen ovale placement accuracy can be improved with robot guidance.
基金Supported by National Natural Science Foundation of P.R.China(50405046,60605028)Shanghai Project of International Cooperation(045107031)the Program for Excellent Young Teachers of Shanghai(04YOHB094)
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.
文摘The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinforcement signal into an evolutionary algorithm.The reinforcement signal is calculated by estimating the optical flow densities in areas of the camera to determine whether they are“dense”or“thin”which has a relationship with the proximity of objects.The results obtained show that the present approach improves the rate of learning compared with a method with a simple reward system and without the evolutionary component.The proposed system was implemented in a virtual robotics system using the CoppeliaSim software and in communication with Python.
基金Sponsored by the Aerospace Technology Innovation Funding(Grant No. CASC0209)
文摘A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative position,velocity and attitude of two unmanned aerial vehicles (UAVs).The second-order divided difference filter which makes use of multidimensional interpolation formulations to approximate the nonlinear transformations could achieve more accurate estimation and faster convergence from inaccurate initial conditions than standard extended Kalman filter.The filter formulation is based on relative motion equations.The global attitude parameterization is given by quarternion,while a generalized three-dimensional attitude representation is used to define the local attitude error.Simulation results are shown to compare the performance of the second-order divided difference filter with a standard extended Kalman filter approach.
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.
文摘The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.
基金supported by the National Natural Science Foundation of China(Grant No.52073222)the Fundamental Research Funds for the Central Universities(Grant No.WUT:104972024JYS0027).
文摘Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in complex environments.To address this problem,we have developed a permanent-magnet-actuated microswarm navigation system to achieve precise control of micro/nanorobots in complex fluid environments.The controlled microswarm is composed of monodisperse Fe_(3)O_(4)@PVP nanoclusters synthesized using the polyol method.These nanoclusters can self-assemble into highly controllable microswarm structures under a rotating magnetic field and are then guided by the robotic system for precise navigation.The system uses visual positioning and motion control to enable real-time dynamic navigation.In experiments,it successfully performed autonomous navigation over a 55 mm distance in a transparent channel,with flow rates ranging from 0 to 10 mm/s.It completed the task in 132 s at an average speed of over 0.45 mm/s,with an average trajectory tracking error of only 0.28 mm.These results demonstrate excellent path accuracy and stability under various flow rate conditions,validating the system’s adaptability and efficiency in fluid environments and highlighting its potential for biomedical applications.This study offers a robust and versatile platform for expanding micro/nanorobot applications in biomedicine.
基金supported by the National Key Research and Development of China(Grant No.2022YFB3805700)the National Natural Science Foundation of China(Grant Nos.12122202 and 12372162)the Fundamental Research Funds for the Central Universities(Grant No.2024CX06021).
文摘In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile sensing ability.In recent years,vision-based tactile sensing technology has been the research hotspot and frontier in the field of tactile perception.Compared to conventional tactile sensing technologies,vision-based tactile sensing technologies are capable of obtaining highquality and high-resolution tactile information at a lower cost,while not being limited by the size and shape of sensors.Several previous articles have reviewed the sensing mechanism and electrical components of vision-based sensors,greatly promoting the innovation of tactile sensing.Different from existing reviews,this article concentrates on the underlying tracking method which converts real-time images into deformation information,including contact,sliding and friction.We will show the history and development of both model-based and model-free tracking methods,among which model-based approaches rely on schematic mechanical theories,and model-free approaches mainly involve machine learning algorithms.Comparing the efficiency and accuracy of existing deformation tracking methods,future research directions of vision-based tactile sensors for smart manipulations and robots are also discussed.
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.
