The visual navigation marks are established purposely,which transfer information to the trained observer in order to navigate.The visual aids to navigation in freshwater could give aid to navigation.In addition,throug...The visual navigation marks are established purposely,which transfer information to the trained observer in order to navigate.The visual aids to navigation in freshwater could give aid to navigation.In addition,through its basic shape,appearance forms and colors,the landscape of navigation waterway is also displayed.The aids to navigation together with channel revetment and other surrounding landscape elements determine the landscape effect of the navigation waterway.Through analyzing the design of aids to navigation features,the design impact factors,the landscape design principles and methods of treatment are proposed in this research,in order to provide some references for the design of future visual aids to navigation.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
There are about 253 million people with visual impairment worldwide.Many of them use a white cane and/or a guide dog as the mobility tool for daily travel.Despite decades of efforts,electronic navigation aid that can ...There are about 253 million people with visual impairment worldwide.Many of them use a white cane and/or a guide dog as the mobility tool for daily travel.Despite decades of efforts,electronic navigation aid that can replace white cane is still research in progress.In this paper,we propose an RGB-D camera based visual positioning system(VPS)for real-time localization of a robotic navigation aid(RNA)in an architectural floor plan for assistive navigation.The core of the system is the combination of a new 6-DOF depth-enhanced visual-inertial odometry(DVIO)method and a particle filter localization(PFL)method.DVIO estimates RNA’s pose by using the data from an RGB-D camera and an inertial measurement unit(IMU).It extracts the floor plane from the camera’s depth data and tightly couples the floor plane,the visual features(with and without depth data),and the IMU’s inertial data in a graph optimization framework to estimate the device’s 6-DOF pose.Due to the use of the floor plane and depth data from the RGB-D camera,DVIO has a better pose estimation accuracy than the conventional VIO method.To reduce the accumulated pose error of DVIO for navigation in a large indoor space,we developed the PFL method to locate RNA in the floor plan.PFL leverages geometric information of the architectural CAD drawing of an indoor space to further reduce the error of the DVIO-estimated pose.Based on VPS,an assistive navigation system is developed for the RNA prototype to assist a visually impaired person in navigating a large indoor space.Experimental results demonstrate that:1)DVIO method achieves better pose estimation accuracy than the state-of-the-art VIO method and performs real-time pose estimation(18 Hz pose update rate)on a UP Board computer;2)PFL reduces the DVIO-accrued pose error by 82.5%on average and allows for accurate wayfinding(endpoint position error≤45 cm)in large indoor spaces.展开更多
Gravity-aided inertial navigation is a hot issue in the applications of underwater autonomous vehicle(UAV). Since the matching process is conducted with a gravity anomaly database tabulated in the form of a digital mo...Gravity-aided inertial navigation is a hot issue in the applications of underwater autonomous vehicle(UAV). Since the matching process is conducted with a gravity anomaly database tabulated in the form of a digital model and the resolution is 2’ × 2’,a filter model based on vehicle position is derived and the particularity of inertial navigation system(INS) output is employed to estimate a parameter in the system model. Meanwhile, the matching algorithm based on point mass filter(PMF) is applied and several optimal selection strategies are discussed. It is obtained that the point mass filter algorithm based on the deterministic resampling method has better practicability. The reliability and the accuracy of the algorithm are verified via simulation tests.展开更多
The navigation problem of the lifting reentry vehicles has attracted much research interest in the past decade. This paper researches the navigation in the blackout zone during the reentry phase of the aircraft, when ...The navigation problem of the lifting reentry vehicles has attracted much research interest in the past decade. This paper researches the navigation in the blackout zone during the reentry phase of the aircraft, when the communication signals are attenuated and even interrupted by the blackout zone. However, when calculating altitude, a pure classic inertial navigation algorithm appears imprecise and divergent. In order to obtain a more precise aircraft altitude, this paper applies an integrated navigation method based on inertial navigation algorithms, which uses drag derived altitude to aid the inertial navigation during the blackout zone. This method can overcome the shortcomings of the inertial navigation system and improve the navigation accuracy. To further improve the navigation accuracy, the applicable condition and the main error factors, such as the atmospheric coefficient error and drag coefficient error are analyzed in detail. Then the damping circuit design of the navigation control system and the damping coefficients determination is introduced. The feasibility of the method is verified by the typical reentry trajectory simulation, and the influence of the iterative times on the accuracy is analyzed. Simulation results show that iterative three times achieves the best effect.展开更多
GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated...GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated navigation systems can be alternatives to GNSS. In this paper,a tightly coupled Camera / IMU algorithm modeled by IEKF( iterated extended kalman filter) is presented. This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly. The developed algorithm is verified by a hybrid simulation,i.e. using inertial data from field test to fuse with simulated image feature measurements. The results show that the tight approach is superior to the loose integration when the image measurements are insufficient( i.e. less than three ground control points).展开更多
Acquisition time of global position system （GPS） receiver, which is the main factor contributes to time to first fix （TTFF）, can be shortened by estimating the Doppler frequency shift through external inertial nav...Acquisition time of global position system （GPS） receiver, which is the main factor contributes to time to first fix （TTFF）, can be shortened by estimating the Doppler frequency shift through external inertial navigation system （INS） information and almanac data and reducing the searching area. The traditional fast acquisition is analyzed, the fast acquisition of the GPS receiver aided is presented by INS information, and the signal is fine captured by spectrum zooming. Then the algorithm is simulated by sampled GPS intermediate frequency （IF） signal and the result verifies that this acquisition can dramatically improve the capability of GPS receiver and reduce its acquisition time.展开更多
文摘The visual navigation marks are established purposely,which transfer information to the trained observer in order to navigate.The visual aids to navigation in freshwater could give aid to navigation.In addition,through its basic shape,appearance forms and colors,the landscape of navigation waterway is also displayed.The aids to navigation together with channel revetment and other surrounding landscape elements determine the landscape effect of the navigation waterway.Through analyzing the design of aids to navigation features,the design impact factors,the landscape design principles and methods of treatment are proposed in this research,in order to provide some references for the design of future visual aids to navigation.
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 NIBIB and the NEI of the National Institutes of Health(R01EB018117)。
文摘There are about 253 million people with visual impairment worldwide.Many of them use a white cane and/or a guide dog as the mobility tool for daily travel.Despite decades of efforts,electronic navigation aid that can replace white cane is still research in progress.In this paper,we propose an RGB-D camera based visual positioning system(VPS)for real-time localization of a robotic navigation aid(RNA)in an architectural floor plan for assistive navigation.The core of the system is the combination of a new 6-DOF depth-enhanced visual-inertial odometry(DVIO)method and a particle filter localization(PFL)method.DVIO estimates RNA’s pose by using the data from an RGB-D camera and an inertial measurement unit(IMU).It extracts the floor plane from the camera’s depth data and tightly couples the floor plane,the visual features(with and without depth data),and the IMU’s inertial data in a graph optimization framework to estimate the device’s 6-DOF pose.Due to the use of the floor plane and depth data from the RGB-D camera,DVIO has a better pose estimation accuracy than the conventional VIO method.To reduce the accumulated pose error of DVIO for navigation in a large indoor space,we developed the PFL method to locate RNA in the floor plan.PFL leverages geometric information of the architectural CAD drawing of an indoor space to further reduce the error of the DVIO-estimated pose.Based on VPS,an assistive navigation system is developed for the RNA prototype to assist a visually impaired person in navigating a large indoor space.Experimental results demonstrate that:1)DVIO method achieves better pose estimation accuracy than the state-of-the-art VIO method and performs real-time pose estimation(18 Hz pose update rate)on a UP Board computer;2)PFL reduces the DVIO-accrued pose error by 82.5%on average and allows for accurate wayfinding(endpoint position error≤45 cm)in large indoor spaces.
基金supported by the National Natural Science Foundation of China(61673060)the National Key R&D Plan(2016YFB0501700)
文摘Gravity-aided inertial navigation is a hot issue in the applications of underwater autonomous vehicle(UAV). Since the matching process is conducted with a gravity anomaly database tabulated in the form of a digital model and the resolution is 2’ × 2’,a filter model based on vehicle position is derived and the particularity of inertial navigation system(INS) output is employed to estimate a parameter in the system model. Meanwhile, the matching algorithm based on point mass filter(PMF) is applied and several optimal selection strategies are discussed. It is obtained that the point mass filter algorithm based on the deterministic resampling method has better practicability. The reliability and the accuracy of the algorithm are verified via simulation tests.
基金supported by the National Natural Science Foundation of China (No.61573059)
文摘The navigation problem of the lifting reentry vehicles has attracted much research interest in the past decade. This paper researches the navigation in the blackout zone during the reentry phase of the aircraft, when the communication signals are attenuated and even interrupted by the blackout zone. However, when calculating altitude, a pure classic inertial navigation algorithm appears imprecise and divergent. In order to obtain a more precise aircraft altitude, this paper applies an integrated navigation method based on inertial navigation algorithms, which uses drag derived altitude to aid the inertial navigation during the blackout zone. This method can overcome the shortcomings of the inertial navigation system and improve the navigation accuracy. To further improve the navigation accuracy, the applicable condition and the main error factors, such as the atmospheric coefficient error and drag coefficient error are analyzed in detail. Then the damping circuit design of the navigation control system and the damping coefficients determination is introduced. The feasibility of the method is verified by the typical reentry trajectory simulation, and the influence of the iterative times on the accuracy is analyzed. Simulation results show that iterative three times achieves the best effect.
基金Sponsored by the National High Technology Research and Development Program(Grant No.2012AA12A209)the National Natural Science Foundation of China(Grant No.41174028,41374033)+2 种基金the Key Laboratory Development Fund from the Ministry of Education of China(Grant No.618-277176)the LIESMARS Special Research Fund,the Research Start-up Fund from Wuhan Univesity(Grant No.618-273438)the Fundamental Research Funds for the Central Universities(Grant No.201161802020002)
文摘GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated navigation systems can be alternatives to GNSS. In this paper,a tightly coupled Camera / IMU algorithm modeled by IEKF( iterated extended kalman filter) is presented. This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly. The developed algorithm is verified by a hybrid simulation,i.e. using inertial data from field test to fuse with simulated image feature measurements. The results show that the tight approach is superior to the loose integration when the image measurements are insufficient( i.e. less than three ground control points).
文摘Acquisition time of global position system （GPS） receiver, which is the main factor contributes to time to first fix （TTFF）, can be shortened by estimating the Doppler frequency shift through external inertial navigation system （INS） information and almanac data and reducing the searching area. The traditional fast acquisition is analyzed, the fast acquisition of the GPS receiver aided is presented by INS information, and the signal is fine captured by spectrum zooming. Then the algorithm is simulated by sampled GPS intermediate frequency （IF） signal and the result verifies that this acquisition can dramatically improve the capability of GPS receiver and reduce its acquisition time.
