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
Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an inte...Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.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
This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars...This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.展开更多
A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path...A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.展开更多
Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small...Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonl...A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.展开更多
This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path plannin...This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.展开更多
A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kal...A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.展开更多
Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated...Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation.Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars,the latter one is becoming a research hotspot.One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference.To solve this problem,an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed.In this method,the rotational SINS error equation in the navigation frame is used as the state model,and the starlight vector and star altitude are used as measurements.Semi-physical simulations are conducted to test the performance of this integrated method.Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS,rotational SINS,and traditional tightly coupled SINS/CNS integrated navigation method.展开更多
With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this pa...With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.展开更多
A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The ran...A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The range of target-to-interceptor speed ratio during target interception is derived when guidance laws are applied in high-speed targets interception,and the effectiveness of negative navigation ratio in the PN-based guidance law is proven analytically in some lemmas.Based on the lemmas,the lateral acceleration command of CPN is defined,and the solution to the appearance of singularity in time-varying navigation ratio is given.The simulation results show that CPN can determine headon engagement(as PN) or tail-chase engagement(as RPN) through initial path angle compared with PN and retro proportional navigation(RPN),and can adjust the value of navigation ratio for head-on engagement or tail-chase engagement.Therefore,the capture region of CPN is larger than that of other guidance laws using PN-based methods.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
This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Second...This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.展开更多
In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the mem...In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.展开更多
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.
基金supported by the National Natural Science Foundation of China(Grant No.61773142).
文摘Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.
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 National Key Research and Development Program of China(2022YFA1004703)the National Natural Science Foundation of China(62088101).
文摘This paper presents a quadcopter system for naviga-tion in outdoor urban environments.The main contributions include the hardware design,the establishment of global occu-pancy grid maps based on millimeter-wave radars,the trajec-tory planning scheme based on optimal virtual tube methods,and the controller structure based on dynamics.The proposed system focuses on utilizing a compact and lightweight quadro-tor with sensors to achieve navigation that conforms to the direction of urban roads with high computational efficiency and safety.Our work is an application of millimeter-wave radars and virtual tube planning for obstacle avoidance in navigation.The validness and effectiveness of the proposed system are verified by experiments.
基金supported by the National Science Fund for Distinguished Young Scholars(52425211)BIT Research Fund Program for Young Scholars(XSQD-202201005).
文摘A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(61773306).
文摘Visual inertial odometry(VIO)problems have been extensively investigated in recent years.Existing VIO methods usually consider the localization or navigation issues of robots or autonomous vehicles in relatively small areas.This paper considers the problem of vision-aided inertial navigation(VIN)for aircrafts equipped with a strapdown inertial navigation system(SINS)and a downward-viewing camera.This is different from the traditional VIO problems in a larger working area with more precise inertial sensors.The goal is to utilize visual information to aid SINS to improve the navigation performance.In the multistate constraint Kalman filter(MSCKF)framework,we introduce an anchor frame to construct necessary models and derive corresponding Jacobians to implement a VIN filter to directly update the position in the Earth-centered Earth-fixed(ECEF)frame and the velocity and attitude in the local level frame by feature measurements.Due to its filtering-based property,the proposed method is naturally low computational demanding and is suitable for applications with high real-time requirements.Simulation and real-world data experiments demonstrate that the proposed method can considerably improve the navigation performance relative to the SINS.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金supported by the National Natural Science Foundation of China (60535010)
文摘A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.
文摘This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.
基金This project was supported by the National Natural Science Foundation of China (40125013 &40376011)
文摘A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.
基金supported by the National Natural Science Foundation of China(61722301)
文摘Strapdown inertial navigation system(SINS)/celestial navigation system(CNS)integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft.In general,SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation.Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars,the latter one is becoming a research hotspot.One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference.To solve this problem,an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed.In this method,the rotational SINS error equation in the navigation frame is used as the state model,and the starlight vector and star altitude are used as measurements.Semi-physical simulations are conducted to test the performance of this integrated method.Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS,rotational SINS,and traditional tightly coupled SINS/CNS integrated navigation method.
文摘With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.
文摘A new proportional navigation(PN) guidance law,called combined proportional navigation(CPN),is proposed.The guidance law is designed to intercept high-speed targets,which is a common case for ballistic targets.The range of target-to-interceptor speed ratio during target interception is derived when guidance laws are applied in high-speed targets interception,and the effectiveness of negative navigation ratio in the PN-based guidance law is proven analytically in some lemmas.Based on the lemmas,the lateral acceleration command of CPN is defined,and the solution to the appearance of singularity in time-varying navigation ratio is given.The simulation results show that CPN can determine headon engagement(as PN) or tail-chase engagement(as RPN) through initial path angle compared with PN and retro proportional navigation(RPN),and can adjust the value of navigation ratio for head-on engagement or tail-chase engagement.Therefore,the capture region of CPN is larger than that of other guidance laws using PN-based methods.
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(5137917651179156)
文摘This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.
基金supported in part by the National Natural Science Foundation of China(No.41876222)。
文摘In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.
