In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenge...In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision avoidance.In this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better performance.During training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario changes.In order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation environment.Experimental results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.展开更多
To address the problem that model uncertainty and unknown time-varying system noise hinder the filtering accuracy of the autonomous navigation system of satellite constellation,an autonomous navigation method of satel...To address the problem that model uncertainty and unknown time-varying system noise hinder the filtering accuracy of the autonomous navigation system of satellite constellation,an autonomous navigation method of satellite constellation based on the Unscented Kalman Filter with Adaptive Forgetting Factors(UKF-AFF)is proposed.The process noise covariance matrix is estimated online with the strategy that combines covariance matching and adaptive adjustment of forgetting factors.The adaptive adjustment coefficient based on squared Mahalanobis distance of state residual is employed to achieve online regulation of forgetting factors,equipping this method with more adaptability.The intersatellite direction vector obtained from photographic observations is introduced to determine the constellation satellite orbit together with the distance measurement to avoid rank deficiency issues.Considering that the number of available measurements varies online with intersatellite visibility in practical applications such as time-varying constellation configurations,the smooth covariance matrix of state correction determined by innovation and gain is adopted and constructed recursively.Stability analysis of the proposed method is also conducted.The effectiveness of the proposed method is verified by the Monte Carlo simulation and comparison experiments.The estimation accuracy of constellation position and velocity of UKF-AFF is improved by 30%and 44%respectively compared to those of the extended Kalman filter,and the method proposed is also better than other several adaptive filtering methods in the presence of significant model uncertainty.展开更多
This article presents a near-Earth satellite orbit estimation method for pico-satellite applications with light-weight and low-power requirements. The method provides orbit information autonomously from magnetometer a...This article presents a near-Earth satellite orbit estimation method for pico-satellite applications with light-weight and low-power requirements. The method provides orbit information autonomously from magnetometer and sun sensor, with an extended Kalman filter （EKF）. Real-time position/velocity parameters are estimated with attitude independently from two quantities： the measured magnitude of the Earth’s magnetic field, and the measured dot product of the magnetic field vector and the sun vector. To guarantee the filter’s effectiveness, it is recommended that the sun sensor should at least have the same level of accuracy as magnetometer. Furthermore, to reduce filter’s computation expense, simplification methods in EKF’s Jacobian calculations are introduced and testified, and a polynomial model for fast magnetic field calculation is developed. With these methods, 50% of the computation expense in dynamic model propagation and 80% of the computation burden in measurement model calculation can be reduced. Tested with simulation data and compared with original magnetometer-only methods, filter achieves faster convergence and higher accuracy by 75% and 30% respectively, and the suggested simplification methods are proved to be harmless to filter’s estimation performance.展开更多
While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous ...While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous navigation in an unknown dynamic environment for a single and a group of three wheeled omnidirectional mobile robots(TWOMRs). The robot has to track a dynamic target while avoiding dynamic obstacles and dynamic walls in an unknown and very dense environment. It adopts a behavior-based controller that consists of four behaviors: "target tracking", "obstacle avoidance", "dynamic wall following" and "avoid robots". The paper considers the problem of kinematic saturation. In addition, it introduces a strategy for predicting the velocity of dynamic obstacles based on two successive measurements of the ultrasonic sensors to calculate the velocity of the obstacle expressed in the sensor frame. Furthermore, the paper proposes a strategy to deal with dynamic walls even when they have U-like or V-like shapes. The approach can also deal with the formation control of a group of robots based on the leader-follower structure and the behavior-based control, where the robots have to get together and maintain a given formation while navigating toward the target, avoiding obstacles and walls in a dynamic environment. The effectiveness of the proposed approaches is demonstrated via simulation.展开更多
This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on ...This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on the advances of the key techniques supporting XNAV,including the navigation pulsar database,the X-ray detection system,and the pulse time of arrival estimation.Moreover,the methods to improve the estimation performance of XNAV are reviewed.Finally,some remarks on the future development of XNAV are provided.展开更多
Libration-point missions have been very useful and successful. Due to the unstable natures of most of these orbits, the long-time stationkeeping demands frequent maneuvers and precise orbit determinations. Earth-based...Libration-point missions have been very useful and successful. Due to the unstable natures of most of these orbits, the long-time stationkeeping demands frequent maneuvers and precise orbit determinations. Earth-based tracking will have to undertake much more responsibilities with the increasing number of libration missions. An autonomous navigation system could offer a better way to decrease the need for Earth-based tracking. Nevertheless, when an autonomous navigation system is applied, there are three important factors affecting autonomous navigation accuracy, i.e., the accuracy of initial conditions, the accuracy of measurements, and the accuracy of onboard dynamics for propagation. This paper focuses on analyzing the influence from the third factor and finding an appropriate navigation dynamics, which can satisfy the requirement of estimation accuracy but not cause too much burden for onboard computation. When considering the restricted three-body model and the bicircular restricted four-body model as navigation dynamics, the astrin- gency is not shown during the simulations. Meanwhile, when considering the influences of the Sun＇s direct and indirect perturbations and the eccentricity of the Moon＇s orbit, a new navigation dynamic model with the standard ephemerides is proposed. The simulation shows the feasibility of the proposed model.展开更多
In this paper a new reactive mechanism based on perception-action bionics for multi-sensory integration applied to Un- manned Aerial Vehicles (UAVs) navigation is proposed.The strategy is inspired by the olfactory bul...In this paper a new reactive mechanism based on perception-action bionics for multi-sensory integration applied to Un- manned Aerial Vehicles (UAVs) navigation is proposed.The strategy is inspired by the olfactory bulb neural activity observed in rabbits subject to external stimuli.The new UAV navigation technique exploits the use of a multiscroll chaotic system which is able to be controlled in real-time towards less complex orbits,like periodic orbits or equilibrium points,considered as perceptive orbits.These are subject to real-time modifications on the basis of environment changes acquired through a Synthetic Aperture Radar (SAR) sensory system.The mathematical details of the approach are given including simulation results in a virtual en- vironment.The results demonstrate the capability of autonomous navigation for UAV based on chaotic bionics theory in com- plex spatial environments.展开更多
With advancements in medical imaging and robotic technology,the idea of fully autonomous diagnosis and treatment has become appealing,from ethereal to tangible.Owing to its characteristics of non-invasiveness,non-radi...With advancements in medical imaging and robotic technology,the idea of fully autonomous diagnosis and treatment has become appealing,from ethereal to tangible.Owing to its characteristics of non-invasiveness,non-radiation,and fast imaging speed,ultrasonography has been increasingly used in clinical practice,such as in obstetrics,gynecology,and surgical puncture.In this paper,we propose a real-time image-based visual servo control scheme using a hybrid slice-to-volume registration method.In this manner,the robot can autonomously locate the ultrasound probe to the desired posture according to preoperational planning,even in the presence of disturbances.The experiments are designed and conducted using a thyroid biopsy phantom model.The results show that the proposed scheme can achieve a refresh rate of up to 30 Hz and a tracking accuracy of(0.52±0.65)mm.展开更多
In a rechargeable wireless sensor network,utilizing the unmanned aerial vehicle(UAV)as a mobile base station(BS)to charge sensors and collect data effectively prolongs the network’s lifetime.In this paper,we jointly ...In a rechargeable wireless sensor network,utilizing the unmanned aerial vehicle(UAV)as a mobile base station(BS)to charge sensors and collect data effectively prolongs the network’s lifetime.In this paper,we jointly optimize the UAV’s flight trajectory and the sensor selection and operation modes to maximize the average data traffic of all sensors within a wireless sensor network(WSN)during finite UAV’s flight time,while ensuring the energy required for each sensor by wireless power transfer(WPT).We consider a practical scenario,where the UAV has no prior knowledge of sensor locations.The UAV performs autonomous navigation based on the status information obtained within the coverage area,which is modeled as a Markov decision process(MDP).The deep Q-network(DQN)is employed to execute the navigation based on the UAV position,the battery level state,channel conditions and current data traffic of sensors within the UAV’s coverage area.Our simulation results demonstrate that the DQN algorithm significantly improves the network performance in terms of the average data traffic and trajectory design.展开更多
Autonomous navigation is a complex challenge that involves the interpretation and analysis of information about the scenario to facilitate the cognitive processes of a robot to perform free trajectories in dynamic env...Autonomous navigation is a complex challenge that involves the interpretation and analysis of information about the scenario to facilitate the cognitive processes of a robot to perform free trajectories in dynamic environments. To solve this, the paper introduces a Case-Based Reasoning methodology to endow robots with an efficient decision structure aiming of selecting the best maneuver to avoid collisions. In particular, Manhattan Distance was implemented to perform the retrieval process in CBR method. Four scenarios were depicted to run a set of experiments in order to validate the functionality of the implemented work. Finally, conclusions emphasize the advantages of CBR methodology to perform autonomous navigation in unknown and uncertain environments.展开更多
In the mobile robotic systems a precise estimate of the robot pose (Cartesian [x y] position plus orientation angle theta) with the intention of the path planning optimization is essential for the correct performance,...In the mobile robotic systems a precise estimate of the robot pose (Cartesian [x y] position plus orientation angle theta) with the intention of the path planning optimization is essential for the correct performance, on the part of the robots, for tasks that are destined to it, especially when intention is for mobile robot autonomous navigation. This work uses a ToF (Time-of-Flight) of the RF digital signal interacting with beacons for computational triangulation in the way to provide a pose estimative at bi-dimensional indoor environment, where GPS system is out of range. It’s a new technology utilization making good use of old ultrasonic ToF methodology that takes advantage of high performance multicore DSP processors to calculate ToF of the order about ns. Sensors data like odometry, compass and the result of triangulation Cartesian estimative, are fused in a Kalman filter in the way to perform optimal estimation and correct robot pose. A mobile robot platform with differential drive and nonholonomic constraints is used as base for state space, plants and measurements models that are used in the simulations and for validation the experiments.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
Sequential images provided by optical cameras are ideal for realizing high-precision autonomous navigation for planetary landings, but due to limited computational resources, a large amount of image information cannot...Sequential images provided by optical cameras are ideal for realizing high-precision autonomous navigation for planetary landings, but due to limited computational resources, a large amount of image information cannot be processed on deep space probes, thus the rich landmark features in the sequential images must be selected. The contribution of landmark features to navigation accuracy is usually measured in terms of observability degrees, but the traditional method only observes the locally optimal landmarks at a single moment, and the navigation accuracy will be affected by the gradual decrease of observability degrees when observing the same landmark several times in a row before landmarks are reoptimized. In this paper, we first establish of autonomous navigation model of planetary landing segment based on sequential images. Then we construct a sequential image observability degree for multiple observations, proving that it is a convex function, and giving the interval of the minimum value point, which guides the selection of landmarks with the highest observability for multiple moments. Finally, numerical simulations were conducted and verified that using sequential image observability degree to optimize landmarks for navigation can achieve higher navigation accuracy than traditional single moment selection methods, and it can provide theoretical support for the sequential image autonomous navigation in the landing segment of deep space exploration.展开更多
Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environ...Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.展开更多
Agricultural vehicles are adopted to undertake farming tasks by traversing along crop rows in the field.Working quality depends significantly on the driving skills of the operator.Automatic guidance has been introduce...Agricultural vehicles are adopted to undertake farming tasks by traversing along crop rows in the field.Working quality depends significantly on the driving skills of the operator.Automatic guidance has been introduced into agriculture to achieve high-accuracy path tracking during the last decades,which contributes considerably to straight-line navigation.The objective of this research was to develop an autonomous navigation controller that allowed movement autonomy for various agricultural vehicles.Three wheel-type vehicles were used as the test platform featuring automatic steering,hydrostatic transmission and speed control,which included a rice transplanter,a high-clearance sprayer and a tractor.A dual-antenna RTK-GNSS receiver was attached to the vehicles to provide spatial information on both positioning and heading by using the RTX service from Trimble.A path planning method was proposed to create a straight-line reference path by giving two points,and the target path was determined according to the vehicle initial status and working assignment.Headland turning was comprehensively taken into account by listing different turn patterns in order to realize autonomous navigation at the headland.The navigation controller hardware was fabricated for program execution,data processing and information communication with peripherals.A human-machine interface was designed for the operator to complete basic setting,path planning and navigation control by providing controls.Field experiments were conducted to evaluate the performance and versatility of the newly developed autonomous navigation controller in guiding agricultural vehicles to follow straight paths and turn at the headland.Results showed that an appropriate turn pattern was automatically executed when finishing straight-line navigation.The lateral error in straight-line tracking was no more than 6 cm,6 cm and 5 cm for the rice transplanter,the high-clearance sprayer and the tractor,respectively.And the maximum lateral RMS error was 3.10 cm,4.75 cm,2.21 cm in terms of straight-line tracking,which indicated that the newly developed autonomous navigation controller was versatile and of high robustness in guiding various agricultural vehicles.展开更多
Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories.Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous pa...Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories.Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous path,which are extremely boring in terms of large-scale fields.The objective of this research was to develop an autonomous navigation system that automatically guided a rice transplanter working along predetermined paths in the field.The rice transplanter used in this research was commercially available and originally manually-operated.An automatic manipulating system was developed instead of manual functions including steering,stop,going forward and reverse.A sensor fusion algorithm was adopted to integrate measurements of the Real-Time Kinematic Global Navigation Satellite System(RTK-GNSS)and Inertial Measurement Unit(IMU),and calculate the absolute moving direction under the UTM coordinate system.A headland turning control method was proposed to ensure a robust turning process considering that the rice transplanter featured a small turning radius and a relatively large slip rate at extreme steering angles.Experiments were designed and conducted to verify the performance of the newly developed autonomous navigation system.Results showed that both lateral and heading errors were less than 8 cm and 3 degrees,respectively,in terms of following straight paths.And headland turns were robustly executed according to the required pattern.展开更多
This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible targets.For the considered navigation system,the position and velocity...This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible targets.For the considered navigation system,the position and velocity of the spacecraft are estimated using an extended Kalman filter(EKF)with the measurements of inter-satellite line-of-sight(LOS)vectors obtained via an onboard star camera.This paper focuses on the selection of the appropriate target at each observation period for the star camera adaptively,such that the performance of the EKF is enhanced.To derive an effective algorithm,a Q-function is designed to select a proper observation region,while a U-function is introduced to rank the targets in the selected region.Both the Q-function and the U-function are constructed based on the sequence of innovations obtained from the EKF.The efficiency of the Q-learning-based target selection algorithm is illustrated via numerical simulations,which show that the presented algorithm outperforms the traditional target selection strategy based on a Cramer-Rao bound(CRB)in the case that the prior knowledge about the target location is inaccurate.展开更多
The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obsta...The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle avoidance.Selecting the correct components is a critical part of the design process.However,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and disadvantages.For example,satellite-based navigation components should be avoided when designing indoor UAVs.Incorporating them in the design brings no added value to the final product and will simply lead to increased cost and power consumption.Another issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar technologies.The aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout conflicts.The paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given requirements.The selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.展开更多
Autonomous navigation of navigation satellite is discussed. The method of auto-orbit determination using the erosslink range and orientation parameters constraining is put forward. On the basis of the analysis of its ...Autonomous navigation of navigation satellite is discussed. The method of auto-orbit determination using the erosslink range and orientation parameters constraining is put forward. On the basis of the analysis of its feasibility, some useful conclusions are given.展开更多
文摘In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision avoidance.In this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better performance.During training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario changes.In order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation environment.Experimental results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.
基金Associate Professor Hongzhuan Qiu for his valuable comments and suggestions in formula derivation and proofreading of this paper.
文摘To address the problem that model uncertainty and unknown time-varying system noise hinder the filtering accuracy of the autonomous navigation system of satellite constellation,an autonomous navigation method of satellite constellation based on the Unscented Kalman Filter with Adaptive Forgetting Factors(UKF-AFF)is proposed.The process noise covariance matrix is estimated online with the strategy that combines covariance matching and adaptive adjustment of forgetting factors.The adaptive adjustment coefficient based on squared Mahalanobis distance of state residual is employed to achieve online regulation of forgetting factors,equipping this method with more adaptability.The intersatellite direction vector obtained from photographic observations is introduced to determine the constellation satellite orbit together with the distance measurement to avoid rank deficiency issues.Considering that the number of available measurements varies online with intersatellite visibility in practical applications such as time-varying constellation configurations,the smooth covariance matrix of state correction determined by innovation and gain is adopted and constructed recursively.Stability analysis of the proposed method is also conducted.The effectiveness of the proposed method is verified by the Monte Carlo simulation and comparison experiments.The estimation accuracy of constellation position and velocity of UKF-AFF is improved by 30%and 44%respectively compared to those of the extended Kalman filter,and the method proposed is also better than other several adaptive filtering methods in the presence of significant model uncertainty.
基金New Century Program for Excellent Talents of Minis-try of Education of China (NCET-06-0514)China Postdoctoral Science Foundation (20081458, 20080431306)
文摘This article presents a near-Earth satellite orbit estimation method for pico-satellite applications with light-weight and low-power requirements. The method provides orbit information autonomously from magnetometer and sun sensor, with an extended Kalman filter （EKF）. Real-time position/velocity parameters are estimated with attitude independently from two quantities： the measured magnitude of the Earth’s magnetic field, and the measured dot product of the magnetic field vector and the sun vector. To guarantee the filter’s effectiveness, it is recommended that the sun sensor should at least have the same level of accuracy as magnetometer. Furthermore, to reduce filter’s computation expense, simplification methods in EKF’s Jacobian calculations are introduced and testified, and a polynomial model for fast magnetic field calculation is developed. With these methods, 50% of the computation expense in dynamic model propagation and 80% of the computation burden in measurement model calculation can be reduced. Tested with simulation data and compared with original magnetometer-only methods, filter achieves faster convergence and higher accuracy by 75% and 30% respectively, and the suggested simplification methods are proved to be harmless to filter’s estimation performance.
文摘While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous navigation in an unknown dynamic environment for a single and a group of three wheeled omnidirectional mobile robots(TWOMRs). The robot has to track a dynamic target while avoiding dynamic obstacles and dynamic walls in an unknown and very dense environment. It adopts a behavior-based controller that consists of four behaviors: "target tracking", "obstacle avoidance", "dynamic wall following" and "avoid robots". The paper considers the problem of kinematic saturation. In addition, it introduces a strategy for predicting the velocity of dynamic obstacles based on two successive measurements of the ultrasonic sensors to calculate the velocity of the obstacle expressed in the sensor frame. Furthermore, the paper proposes a strategy to deal with dynamic walls even when they have U-like or V-like shapes. The approach can also deal with the formation control of a group of robots based on the leader-follower structure and the behavior-based control, where the robots have to get together and maintain a given formation while navigating toward the target, avoiding obstacles and walls in a dynamic environment. The effectiveness of the proposed approaches is demonstrated via simulation.
基金the National Natural Science Foundation of China(No.61703413)the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3078).
文摘This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on the advances of the key techniques supporting XNAV,including the navigation pulsar database,the X-ray detection system,and the pulse time of arrival estimation.Moreover,the methods to improve the estimation performance of XNAV are reviewed.Finally,some remarks on the future development of XNAV are provided.
基金was supported by the National Natural Science Foundation of China(No.61021002).
文摘Libration-point missions have been very useful and successful. Due to the unstable natures of most of these orbits, the long-time stationkeeping demands frequent maneuvers and precise orbit determinations. Earth-based tracking will have to undertake much more responsibilities with the increasing number of libration missions. An autonomous navigation system could offer a better way to decrease the need for Earth-based tracking. Nevertheless, when an autonomous navigation system is applied, there are three important factors affecting autonomous navigation accuracy, i.e., the accuracy of initial conditions, the accuracy of measurements, and the accuracy of onboard dynamics for propagation. This paper focuses on analyzing the influence from the third factor and finding an appropriate navigation dynamics, which can satisfy the requirement of estimation accuracy but not cause too much burden for onboard computation. When considering the restricted three-body model and the bicircular restricted four-body model as navigation dynamics, the astrin- gency is not shown during the simulations. Meanwhile, when considering the influences of the Sun＇s direct and indirect perturbations and the eccentricity of the Moon＇s orbit, a new navigation dynamic model with the standard ephemerides is proposed. The simulation shows the feasibility of the proposed model.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2006AA12A108)"Multi-sensor Integrated Navigation in Aeronautics Field" the Ministry of Science and Technology of ChinaCSC International Scholarship (2008104769) Chinese Scholarship CouncilInternational Postgraduate Research Scholarship Program (2009800778591) from Australian Government.
文摘In this paper a new reactive mechanism based on perception-action bionics for multi-sensory integration applied to Un- manned Aerial Vehicles (UAVs) navigation is proposed.The strategy is inspired by the olfactory bulb neural activity observed in rabbits subject to external stimuli.The new UAV navigation technique exploits the use of a multiscroll chaotic system which is able to be controlled in real-time towards less complex orbits,like periodic orbits or equilibrium points,considered as perceptive orbits.These are subject to real-time modifications on the basis of environment changes acquired through a Synthetic Aperture Radar (SAR) sensory system.The mathematical details of the approach are given including simulation results in a virtual en- vironment.The results demonstrate the capability of autonomous navigation for UAV based on chaotic bionics theory in com- plex spatial environments.
基金the Shenzhen Science and Technology Program(No.RCYX20200714114736115)the Longgang District Medical and Health Science and Technology Project of Shenzhen(No.LGWJ2021-036)。
文摘With advancements in medical imaging and robotic technology,the idea of fully autonomous diagnosis and treatment has become appealing,from ethereal to tangible.Owing to its characteristics of non-invasiveness,non-radiation,and fast imaging speed,ultrasonography has been increasingly used in clinical practice,such as in obstetrics,gynecology,and surgical puncture.In this paper,we propose a real-time image-based visual servo control scheme using a hybrid slice-to-volume registration method.In this manner,the robot can autonomously locate the ultrasound probe to the desired posture according to preoperational planning,even in the presence of disturbances.The experiments are designed and conducted using a thyroid biopsy phantom model.The results show that the proposed scheme can achieve a refresh rate of up to 30 Hz and a tracking accuracy of(0.52±0.65)mm.
文摘In a rechargeable wireless sensor network,utilizing the unmanned aerial vehicle(UAV)as a mobile base station(BS)to charge sensors and collect data effectively prolongs the network’s lifetime.In this paper,we jointly optimize the UAV’s flight trajectory and the sensor selection and operation modes to maximize the average data traffic of all sensors within a wireless sensor network(WSN)during finite UAV’s flight time,while ensuring the energy required for each sensor by wireless power transfer(WPT).We consider a practical scenario,where the UAV has no prior knowledge of sensor locations.The UAV performs autonomous navigation based on the status information obtained within the coverage area,which is modeled as a Markov decision process(MDP).The deep Q-network(DQN)is employed to execute the navigation based on the UAV position,the battery level state,channel conditions and current data traffic of sensors within the UAV’s coverage area.Our simulation results demonstrate that the DQN algorithm significantly improves the network performance in terms of the average data traffic and trajectory design.
文摘Autonomous navigation is a complex challenge that involves the interpretation and analysis of information about the scenario to facilitate the cognitive processes of a robot to perform free trajectories in dynamic environments. To solve this, the paper introduces a Case-Based Reasoning methodology to endow robots with an efficient decision structure aiming of selecting the best maneuver to avoid collisions. In particular, Manhattan Distance was implemented to perform the retrieval process in CBR method. Four scenarios were depicted to run a set of experiments in order to validate the functionality of the implemented work. Finally, conclusions emphasize the advantages of CBR methodology to perform autonomous navigation in unknown and uncertain environments.
文摘In the mobile robotic systems a precise estimate of the robot pose (Cartesian [x y] position plus orientation angle theta) with the intention of the path planning optimization is essential for the correct performance, on the part of the robots, for tasks that are destined to it, especially when intention is for mobile robot autonomous navigation. This work uses a ToF (Time-of-Flight) of the RF digital signal interacting with beacons for computational triangulation in the way to provide a pose estimative at bi-dimensional indoor environment, where GPS system is out of range. It’s a new technology utilization making good use of old ultrasonic ToF methodology that takes advantage of high performance multicore DSP processors to calculate ToF of the order about ns. Sensors data like odometry, compass and the result of triangulation Cartesian estimative, are fused in a Kalman filter in the way to perform optimal estimation and correct robot pose. A mobile robot platform with differential drive and nonholonomic constraints is used as base for state space, plants and measurements models that are used in the simulations and for validation the experiments.
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(Grant Number U20B2055)the National Natural Science Fund for Distinguished Young Scholars of China(Grant Number 61525301)
文摘Sequential images provided by optical cameras are ideal for realizing high-precision autonomous navigation for planetary landings, but due to limited computational resources, a large amount of image information cannot be processed on deep space probes, thus the rich landmark features in the sequential images must be selected. The contribution of landmark features to navigation accuracy is usually measured in terms of observability degrees, but the traditional method only observes the locally optimal landmarks at a single moment, and the navigation accuracy will be affected by the gradual decrease of observability degrees when observing the same landmark several times in a row before landmarks are reoptimized. In this paper, we first establish of autonomous navigation model of planetary landing segment based on sequential images. Then we construct a sequential image observability degree for multiple observations, proving that it is a convex function, and giving the interval of the minimum value point, which guides the selection of landmarks with the highest observability for multiple moments. Finally, numerical simulations were conducted and verified that using sequential image observability degree to optimize landmarks for navigation can achieve higher navigation accuracy than traditional single moment selection methods, and it can provide theoretical support for the sequential image autonomous navigation in the landing segment of deep space exploration.
基金supported by the Sichuan Science and Technology Program(2025ZNSFSC0005).
文摘Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.
基金The authors acknowledge that this work was financially supported by National Key Research and Development Program of China Sub-project(2017YFD0700405)Key R&D Project of Shandong Province(2019JZZY010734)+2 种基金National Natural Science Foundation of China(31501230)National Natural Science Foundation of China(51905318)Shandong Province Science and Technology Planning Project of Higher Education(J17KA145).
文摘Agricultural vehicles are adopted to undertake farming tasks by traversing along crop rows in the field.Working quality depends significantly on the driving skills of the operator.Automatic guidance has been introduced into agriculture to achieve high-accuracy path tracking during the last decades,which contributes considerably to straight-line navigation.The objective of this research was to develop an autonomous navigation controller that allowed movement autonomy for various agricultural vehicles.Three wheel-type vehicles were used as the test platform featuring automatic steering,hydrostatic transmission and speed control,which included a rice transplanter,a high-clearance sprayer and a tractor.A dual-antenna RTK-GNSS receiver was attached to the vehicles to provide spatial information on both positioning and heading by using the RTX service from Trimble.A path planning method was proposed to create a straight-line reference path by giving two points,and the target path was determined according to the vehicle initial status and working assignment.Headland turning was comprehensively taken into account by listing different turn patterns in order to realize autonomous navigation at the headland.The navigation controller hardware was fabricated for program execution,data processing and information communication with peripherals.A human-machine interface was designed for the operator to complete basic setting,path planning and navigation control by providing controls.Field experiments were conducted to evaluate the performance and versatility of the newly developed autonomous navigation controller in guiding agricultural vehicles to follow straight paths and turn at the headland.Results showed that an appropriate turn pattern was automatically executed when finishing straight-line navigation.The lateral error in straight-line tracking was no more than 6 cm,6 cm and 5 cm for the rice transplanter,the high-clearance sprayer and the tractor,respectively.And the maximum lateral RMS error was 3.10 cm,4.75 cm,2.21 cm in terms of straight-line tracking,which indicated that the newly developed autonomous navigation controller was versatile and of high robustness in guiding various agricultural vehicles.
基金This research was financially supported by National Natural Science Foundation of China(No.31501230)Shandong Province Natural Science Foundation of China for Youths(No.ZR2014CQ058)+1 种基金the National Key Research and Development Program of China Sub-project(No.2017YFD0700405)Shandong Province Science and Technology Planning Project of Higher Education(No.J17KA145).
文摘Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories.Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous path,which are extremely boring in terms of large-scale fields.The objective of this research was to develop an autonomous navigation system that automatically guided a rice transplanter working along predetermined paths in the field.The rice transplanter used in this research was commercially available and originally manually-operated.An automatic manipulating system was developed instead of manual functions including steering,stop,going forward and reverse.A sensor fusion algorithm was adopted to integrate measurements of the Real-Time Kinematic Global Navigation Satellite System(RTK-GNSS)and Inertial Measurement Unit(IMU),and calculate the absolute moving direction under the UTM coordinate system.A headland turning control method was proposed to ensure a robust turning process considering that the rice transplanter featured a small turning radius and a relatively large slip rate at extreme steering angles.Experiments were designed and conducted to verify the performance of the newly developed autonomous navigation system.Results showed that both lateral and heading errors were less than 8 cm and 3 degrees,respectively,in terms of following straight paths.And headland turns were robustly executed according to the required pattern.
基金supported by the National Natural Science Foundation under Grant Nos.61573059,61525301,61690215。
文摘This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible targets.For the considered navigation system,the position and velocity of the spacecraft are estimated using an extended Kalman filter(EKF)with the measurements of inter-satellite line-of-sight(LOS)vectors obtained via an onboard star camera.This paper focuses on the selection of the appropriate target at each observation period for the star camera adaptively,such that the performance of the EKF is enhanced.To derive an effective algorithm,a Q-function is designed to select a proper observation region,while a U-function is introduced to rank the targets in the selected region.Both the Q-function and the U-function are constructed based on the sequence of innovations obtained from the EKF.The efficiency of the Q-learning-based target selection algorithm is illustrated via numerical simulations,which show that the presented algorithm outperforms the traditional target selection strategy based on a Cramer-Rao bound(CRB)in the case that the prior knowledge about the target location is inaccurate.
文摘The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle avoidance.Selecting the correct components is a critical part of the design process.However,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and disadvantages.For example,satellite-based navigation components should be avoided when designing indoor UAVs.Incorporating them in the design brings no added value to the final product and will simply lead to increased cost and power consumption.Another issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar technologies.The aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout conflicts.The paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given requirements.The selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.
文摘Autonomous navigation of navigation satellite is discussed. The method of auto-orbit determination using the erosslink range and orientation parameters constraining is put forward. On the basis of the analysis of its feasibility, some useful conclusions are given.
