This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three...This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).展开更多
We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reco...We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.展开更多
The navigation system plays a pivotal role in guiding aircraft along designated routes,ensuring precise and punctual arrival at destinations.The integration of scene matching with an inertial navigation system enhance...The navigation system plays a pivotal role in guiding aircraft along designated routes,ensuring precise and punctual arrival at destinations.The integration of scene matching with an inertial navigation system enhances the capability of providing a dependable guarantee for success-ful accomplishment of flight missions.Nonetheless,assuring reliability in scene matching encoun-ters significant challenges in areas characterized by repetitive or weak textures.To tackle these challenges,we propose a novel method to assess the reliability of scene matching based on the dis-tinctive characteristics of correlation peaks.The proposed method leverages the fact that the sim-ilarity of the optimal matching result is significantly higher than that of the surrounding area,and three novel indicators(e.g.,relative height,slope of a correlation peak,and ratio of a sub peak to the main peak)are determined to conjointly evaluate the reliability of scene matching.The pro-posed method entails matching a real-time image with a reference image to generate a correlation surface.A correlation peak is then obtained by extracting the portion of the correlation surface exhibiting a significant gradient.Additionally,the matching reliability is determined by considering the relative height,slope,and ratio of the peak collectively.Exhaustive experimental results with two sets of data demonstrate that the proposed method significantly outperforms traditional approaches in terms of precision,recall,and F1-score.These experiments also establish the efficacy of the proposed method in achieving reliable matching in challenging environments characterized by repetitive and weak textures.This enhancement holds the potential to significantly elevate scene-matching-based navigation.展开更多
Obtaining absolute pose based on pre-loaded satellite images is one of the important means of autonomous navigation for small Unmanned Aerial Vehicles(UAVs)in Global Navigation Satellite System(GNSS)denied environment...Obtaining absolute pose based on pre-loaded satellite images is one of the important means of autonomous navigation for small Unmanned Aerial Vehicles(UAVs)in Global Navigation Satellite System(GNSS)denied environments.Most of the previous works have tended to build Convolutional Neural Networks(CNNs)to extract features and then directly regress the pose,which will fail when solving the challenges caused by the huge viewpoint and size differences between“UAV-satellite”image pairs in real-world scenarios.Therefore,this paper proposes a probability distribution/regression integrated deep model with the attention-guided triple fusion mechanism,which estimates discrete distributions in pose space and three-dimensional vectors in translation space.In order to overcome the shortage of the relevant dataset,this paper simulates image datasets captured by UAVs with forward-facing cameras during target searching and autonomous attacking.The effectiveness,superiority,and robustness of the proposed method are verified by simulated datasets and flight tests.展开更多
Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation...Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.展开更多
A scheme of guidance and control is presented to meet the requirements for automatic landing of unmanned aerial vehicles (UAVs) based on the airborne digital flight control system and radio tracker on ground station. ...A scheme of guidance and control is presented to meet the requirements for automatic landing of unmanned aerial vehicles (UAVs) based on the airborne digital flight control system and radio tracker on ground station. An automatic landing system is realized for an unmanned aerial vehicle. The results of real time simulation and flight test are given to illustrate the effectiveness and availability of the scheme. Results meet all the requirements for automatic landing of the unmanned aerial vehicle.展开更多
In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on t...In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.展开更多
Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are eas...Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.展开更多
This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is develo...This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is developed that is updated in real-time with a horizon of three waypoints. The purpose of DWN is to overcome a problem that we find in existing WN for small-class fixed-wing unmanned aerial vehicles (UAV) of not accurately reaching waypoints. This problem results at times in high overshoot and, in the presence of wind disturbances, it can cause a vehicle to miss the waypoint and swirl around it. To prevent this, the DWN creates “new waypoints” that are in the background, called turning points. Examples illustrate the improvement of the performance of WN achieved using the DWN algorithm in terms of the targeting of waypoints while reducing fuel and time.展开更多
In aerial robots＇ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from ...In aerial robots＇ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from almost unmanageable to be partly solved, though not fully, as per the requirement. In this parametric approach, a multi-scale least square method is formulated first. By propagating as well as improving the parameters down from layer to layer of the image pyramid, a new global feature line can then be detected to parameterize the attitude of the robots. Furthermore, this approach paves the way for segmenting the image into distinct parts, which can be realized by deploying a Bayesian classifier on the picture cell level. Comparison with the Hough transform based method in terms of robustness and precision shows that this multi-scale least square algorithm is considerably more robust to noises. Some discussions are also given.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
The History of the transatlantic flights goes back to 1919 and began with a flight performed from Newfoundland to Lisbon;two weeks later another flight was performed between Newfoundland and Ireland. On 1922, the Port...The History of the transatlantic flights goes back to 1919 and began with a flight performed from Newfoundland to Lisbon;two weeks later another flight was performed between Newfoundland and Ireland. On 1922, the Portuguese airmen Gago Coutinho and Sacadura Cabral crossed the South Atlantic Ocean by air in a flight performed exclusively with internal means of navigation: a new instrument that consisted in a type of sextant improved with two spirit levels to provide an artificial horizon and also with the help of a “path corrector”. Despite this journey had lasted 79 days to cross South Atlantic Ocean, their flight time was only 62:26 minutes, and they’ve flown 8,383 nautical miles, using 3 different hydroplanes christened: Lusitania, Pátria and Santa Cruz. Despite this journey had lasted 79 days, their flight time was only 62 h 26 m;they’ve flown 8,383 nautical miles using 3 different hydroplanes christened: Lusitania, Pátria and Santa Cruz. The new artificial horizon sextant had proven itself while flying over the ocean, without external references.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61273054,60975072)the National Basic Research Program of China("973" Project)(Grant No.2013CB035503)+3 种基金the Program for New Century Excellent Talents in University of China(Grant No.NCET-10-0021)the Top-Notch Young Talents Program of Chinathe Fundamental Research Funds for the Central Universities of Chinathe Aeronautical Foundation of China(Grant No.20115151019)
文摘This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).
基金funding from the Australian Government,via grant AUSMURIB000001 associated with ONR MURI Grant N00014-19-1-2571。
文摘We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.
基金supported by the National Natural Science Foundation of China (No.42271446).
文摘The navigation system plays a pivotal role in guiding aircraft along designated routes,ensuring precise and punctual arrival at destinations.The integration of scene matching with an inertial navigation system enhances the capability of providing a dependable guarantee for success-ful accomplishment of flight missions.Nonetheless,assuring reliability in scene matching encoun-ters significant challenges in areas characterized by repetitive or weak textures.To tackle these challenges,we propose a novel method to assess the reliability of scene matching based on the dis-tinctive characteristics of correlation peaks.The proposed method leverages the fact that the sim-ilarity of the optimal matching result is significantly higher than that of the surrounding area,and three novel indicators(e.g.,relative height,slope of a correlation peak,and ratio of a sub peak to the main peak)are determined to conjointly evaluate the reliability of scene matching.The pro-posed method entails matching a real-time image with a reference image to generate a correlation surface.A correlation peak is then obtained by extracting the portion of the correlation surface exhibiting a significant gradient.Additionally,the matching reliability is determined by considering the relative height,slope,and ratio of the peak collectively.Exhaustive experimental results with two sets of data demonstrate that the proposed method significantly outperforms traditional approaches in terms of precision,recall,and F1-score.These experiments also establish the efficacy of the proposed method in achieving reliable matching in challenging environments characterized by repetitive and weak textures.This enhancement holds the potential to significantly elevate scene-matching-based navigation.
基金supported by the National Natural Science Foundation of China(No.61973033)the Chongqing Natural Science Foundation,China(No.cstc2021jcyjmsxmX0737).
文摘Obtaining absolute pose based on pre-loaded satellite images is one of the important means of autonomous navigation for small Unmanned Aerial Vehicles(UAVs)in Global Navigation Satellite System(GNSS)denied environments.Most of the previous works have tended to build Convolutional Neural Networks(CNNs)to extract features and then directly regress the pose,which will fail when solving the challenges caused by the huge viewpoint and size differences between“UAV-satellite”image pairs in real-world scenarios.Therefore,this paper proposes a probability distribution/regression integrated deep model with the attention-guided triple fusion mechanism,which estimates discrete distributions in pose space and three-dimensional vectors in translation space.In order to overcome the shortage of the relevant dataset,this paper simulates image datasets captured by UAVs with forward-facing cameras during target searching and autonomous attacking.The effectiveness,superiority,and robustness of the proposed method are verified by simulated datasets and flight tests.
基金supported by the State Key Laboratory of Geo-Information Engineering(SKLGIE2022-Z-2-1)the National Natural Science Foundation of China(41674024,42174036).
文摘Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.
文摘A scheme of guidance and control is presented to meet the requirements for automatic landing of unmanned aerial vehicles (UAVs) based on the airborne digital flight control system and radio tracker on ground station. An automatic landing system is realized for an unmanned aerial vehicle. The results of real time simulation and flight test are given to illustrate the effectiveness and availability of the scheme. Results meet all the requirements for automatic landing of the unmanned aerial vehicle.
文摘In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.
基金National Natural Science Foundation of China(Grant No.62203111)the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(Grant No.21P01)the Foundation of Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology,Ministry of Education,China(Grant No.SEU-MIAN-202101)to provide fund for conducting experiments。
文摘Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.
文摘This paper considers a variation on the Dubins path problem and proposes an improved waypoint navigation (WN) algorithm called Dubins waypoint navigation (DWN). Based on the Dubins path problem, an algorithm is developed that is updated in real-time with a horizon of three waypoints. The purpose of DWN is to overcome a problem that we find in existing WN for small-class fixed-wing unmanned aerial vehicles (UAV) of not accurately reaching waypoints. This problem results at times in high overshoot and, in the presence of wind disturbances, it can cause a vehicle to miss the waypoint and swirl around it. To prevent this, the DWN creates “new waypoints” that are in the background, called turning points. Examples illustrate the improvement of the performance of WN achieved using the DWN algorithm in terms of the targeting of waypoints while reducing fuel and time.
文摘In aerial robots＇ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from almost unmanageable to be partly solved, though not fully, as per the requirement. In this parametric approach, a multi-scale least square method is formulated first. By propagating as well as improving the parameters down from layer to layer of the image pyramid, a new global feature line can then be detected to parameterize the attitude of the robots. Furthermore, this approach paves the way for segmenting the image into distinct parts, which can be realized by deploying a Bayesian classifier on the picture cell level. Comparison with the Hough transform based method in terms of robustness and precision shows that this multi-scale least square algorithm is considerably more robust to noises. Some discussions are also given.
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The History of the transatlantic flights goes back to 1919 and began with a flight performed from Newfoundland to Lisbon;two weeks later another flight was performed between Newfoundland and Ireland. On 1922, the Portuguese airmen Gago Coutinho and Sacadura Cabral crossed the South Atlantic Ocean by air in a flight performed exclusively with internal means of navigation: a new instrument that consisted in a type of sextant improved with two spirit levels to provide an artificial horizon and also with the help of a “path corrector”. Despite this journey had lasted 79 days to cross South Atlantic Ocean, their flight time was only 62:26 minutes, and they’ve flown 8,383 nautical miles, using 3 different hydroplanes christened: Lusitania, Pátria and Santa Cruz. Despite this journey had lasted 79 days, their flight time was only 62 h 26 m;they’ve flown 8,383 nautical miles using 3 different hydroplanes christened: Lusitania, Pátria and Santa Cruz. The new artificial horizon sextant had proven itself while flying over the ocean, without external references.
