Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a t...Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special point.Secondly,a calculation model of three-impulse contingency return trajectories is established.Then,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics model.Finally,the performance of the proposed methods is verified by numerical simulation.The results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy condition.Due to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed expeditiously.These findings can be used for the design of contingency return trajectories in future manned lunar landing missions.展开更多
1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace c...1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace complexity, and considerable challenges for Air Traffic Control(ATC). As the fundamental technique of the ATC system, Flight Trajectory Prediction(FTP) forecasts future traffic dynamics to support critical applications(such as conflict detection), and also serves as a cornerstone for future Trajectory-based Operations(TBO).展开更多
In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat...In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.展开更多
The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-d...The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.展开更多
Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequent...Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.展开更多
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framin...Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framingham Heart Study(FHS)is the longest-running cardiovascular epidemiological study,starting in 1948.展开更多
Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determ...Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.展开更多
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numer...The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numerous issues present in existing methods for generating effective excavation paths,this paper proposes a trajectory generation method for excavators based on imitation learning,using the mole as a bionic prototype.Given the high excavation efficiency of moles,this paper first analyzes the structural characteristics of the mole’s forelimbs,its digging principles,morphology,and trajectory patterns.Subsequently,a higher-order polynomial is employed to fit and optimize the mole’s excavation trajectory.Next,imitation learning is conducted on sample trajectories based on Dynamic Movement Primitives,followed by the introduction of an obstacle avoidance algorithm.Simulation experiments and comparisons demonstrate that the mole-inspired trajectory method used in this paper performs well and possesses the ability to generate obstacle avoidance trajectories,as well as the convenience of transferring across different machine models.展开更多
To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking contro...To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.展开更多
Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,a...Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,are limited by a high center of gravity,which increases the risk of rollover.Road bulges,sinkholes,and unexpected debris all present additional challenges for autonomous trucks’operational design,which current perception and decisionmaking algorithms often overlook.To mitigate rollover risks and improve adaptability to damaged roads,this paper presents a novel Road Obstacle-Involved Trajectory Planner(ROITP).The planner categorizes road obstacles using a learning-based algorithm.A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics.Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.展开更多
This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bound...This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bounded gain is proposed by using a new time-varying scaling function.Moreover,a same-side performance function and a novel barrier Lyapunov function are incorporated into the control algorithm,which can compress the feasible domain of tracking error to minimize the overshoot and solve the difficult in tracking error not converging to zero simultaneously.The proposed scheme guarantees the airship capable of operating autonomously with satisfactory transient performance and tracking accuracy,where the performance parameters can be designed artificially and link to the physical process directly.Finally,the effectiveness of the proposed control scheme is verified by theoretical analysis and numerical simulation.展开更多
In this paper,we investigate the application of the Unmanned Aerial Vehicle(UAV)-enabled relaying system in emergency communications,where one UAV is applied as a relay to help transmit information from ground users t...In this paper,we investigate the application of the Unmanned Aerial Vehicle(UAV)-enabled relaying system in emergency communications,where one UAV is applied as a relay to help transmit information from ground users to a Base Station(BS).We maximize the total transmitted data from the users to the BS,by optimizing the user communication scheduling and association along with the power allocation and the trajectory of the UAV.To solve this non-convex optimization problem,we propose the traditional Convex Optimization(CO)and the Reinforcement Learning(RL)-based approaches.Specifically,we apply the block coordinate descent and successive convex approximation techniques in the CO approach,while applying the soft actor-critic algorithm in the RL approach.The simulation results show that both approaches can solve the proposed optimization problem and obtain good results.Moreover,the RL approach establishes emergency communications more rapidly than the CO approach once the training process has been completed.展开更多
Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment....Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment.With the aim to conveniently and accurately segment demonstration trajectories,a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model(BP-ARHMM)algorithm and generalised time warping(GTW)algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data.This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task.Then,it adopts the BP-AR-HMM algorithm to segment the demonstration trajectories,acquire the contained motion primitives,and establish the related task library.This segmentation approach is validated on the 6-degree-of-freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task.The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy.展开更多
Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned a...Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.展开更多
In task offloading,the movement of vehicles causes the switching of connected RSUs and servers,which may lead to task offloading failure or high service delay.In this paper,we analyze the impact of vehicle movements o...In task offloading,the movement of vehicles causes the switching of connected RSUs and servers,which may lead to task offloading failure or high service delay.In this paper,we analyze the impact of vehicle movements on task offloading and reveal that data preparation time for task execution can be minimized via forward-looking scheduling.Then,a Bi-LSTM-based model is proposed to predict the trajectories of vehicles.The service area is divided into several equal-sized grids.If the actual position of the vehicle and the predicted position by the model belong to the same grid,the prediction is considered correct,thereby reducing the difficulty of vehicle trajectory prediction.Moreover,we propose a scheduling strategy for delay optimization based on the vehicle trajectory prediction.Considering the inevitable prediction error,we take some edge servers around the predicted area as candidate execution servers and the data required for task execution are backed up to these candidate servers,thereby reducing the impact of prediction deviations on task offloading and converting the modest increase of resource overheads into delay reduction in task offloading.Simulation results show that,compared with other classical schemes,the proposed strategy has lower average task offloading delays.展开更多
Based on a new bilinear equation,we investigated some new dynamic behaviors of the(2+1)-dimensional shallow water wave model,such as hybridization behavior between different solitons,trajectory equations for lump coll...Based on a new bilinear equation,we investigated some new dynamic behaviors of the(2+1)-dimensional shallow water wave model,such as hybridization behavior between different solitons,trajectory equations for lump collisions,and evolution behavior of multi-breathers.Firstly,the N-soliton solution of Ito equation is studied,and some high-order breather waves can be obtained from the N-soliton solutions through paired-complexification of parameters.Secondly,the high-order lump solutions and the hybrid solutions are obtained by employing the long-wave limit method,and the motion velocity and trajectory equations of high-order lump waves are analyzed.Moreover,based on the trajectory equations of the higher-order lump solutions,we give and prove the trajectory theorem of 1-lump before and after interaction with nsoliton.Finally,we obtain some new lump solutions from the multi-solitons by constructing a new test function and using the parameter limit method.Meanwhile,some evolutionary behaviors of the obtained solutions are shown through a large number of three-dimensional graphs with different and appropriate parameters.展开更多
Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article...Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.展开更多
This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated ...This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.展开更多
基金co-supported by the National Natural Science Foundation of China(No.12072365)the Technology Innovation Team of Manned Space Engineering,China。
文摘Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special point.Secondly,a calculation model of three-impulse contingency return trajectories is established.Then,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics model.Finally,the performance of the proposed methods is verified by numerical simulation.The results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy condition.Due to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed expeditiously.These findings can be used for the design of contingency return trajectories in future manned lunar landing missions.
文摘1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace complexity, and considerable challenges for Air Traffic Control(ATC). As the fundamental technique of the ATC system, Flight Trajectory Prediction(FTP) forecasts future traffic dynamics to support critical applications(such as conflict detection), and also serves as a cornerstone for future Trajectory-based Operations(TBO).
文摘In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.
基金supported by the National Key R&D Program of China(No.2022YFB3104502)the National Natural Science Foundation of China(No.62301251)+2 种基金the Natural Science Foundation of Jiangsu Province of China under Project(No.BK20220883)the open research fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2024D04)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.
基金supported by the National Natural Science Foundation of China(No.62203256)。
文摘Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.
基金supported by the Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
文摘Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framingham Heart Study(FHS)is the longest-running cardiovascular epidemiological study,starting in 1948.
基金supported by the National Natural Science Foundation of China(Grant Nos.52425211,52272360,and 52472394)Chongqing Natural Science Foundation(CSTB2023NSCQ-MSX0300)。
文摘Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.
基金supported by Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
基金supported by the National Science Foundation of China(Grant No.52375246,No.52372428,No.52105100)Guangxi Science and Technology Program(Grant No.2023AB09014)Jilin Province Science and Technology Development Program,(Grant No.20230201094GX,No.20230201069GX).
文摘The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numerous issues present in existing methods for generating effective excavation paths,this paper proposes a trajectory generation method for excavators based on imitation learning,using the mole as a bionic prototype.Given the high excavation efficiency of moles,this paper first analyzes the structural characteristics of the mole’s forelimbs,its digging principles,morphology,and trajectory patterns.Subsequently,a higher-order polynomial is employed to fit and optimize the mole’s excavation trajectory.Next,imitation learning is conducted on sample trajectories based on Dynamic Movement Primitives,followed by the introduction of an obstacle avoidance algorithm.Simulation experiments and comparisons demonstrate that the mole-inspired trajectory method used in this paper performs well and possesses the ability to generate obstacle avoidance trajectories,as well as the convenience of transferring across different machine models.
基金support of the National Natural Science Foundation of China(No.12032012)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China。
文摘To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.
基金Supported by National Natural Science Foundation of China (Grant Nos. 52072215, 52221005, 52272386)Beijing Municipal Natrual Science Foundation (Grant No. L243025)+2 种基金National Key R&D Program of China (Grant No. 2022YFB2503003)State Key Laboratory of Intelligent Green Vehicle and Mobilityfundamental Research Funds for the Central Universities
文摘Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,are limited by a high center of gravity,which increases the risk of rollover.Road bulges,sinkholes,and unexpected debris all present additional challenges for autonomous trucks’operational design,which current perception and decisionmaking algorithms often overlook.To mitigate rollover risks and improve adaptability to damaged roads,this paper presents a novel Road Obstacle-Involved Trajectory Planner(ROITP).The planner categorizes road obstacles using a learning-based algorithm.A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics.Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.
基金supported by the National Natural Science Foundation of China(Nos.51775021,52302511)the Fundamental Research Funds for the Central Universities,China(Nos.501JCGG2024129003,501JCGG2024129005,501JCGG2024129006),the Fundamental Research Funds for the Central Universities,China(No.YWF-24-JC-09)the National Key Research and Development Program of China(No.2018YFC1506401)。
文摘This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bounded gain is proposed by using a new time-varying scaling function.Moreover,a same-side performance function and a novel barrier Lyapunov function are incorporated into the control algorithm,which can compress the feasible domain of tracking error to minimize the overshoot and solve the difficult in tracking error not converging to zero simultaneously.The proposed scheme guarantees the airship capable of operating autonomously with satisfactory transient performance and tracking accuracy,where the performance parameters can be designed artificially and link to the physical process directly.Finally,the effectiveness of the proposed control scheme is verified by theoretical analysis and numerical simulation.
基金supported in part by the Shenzhen Basic Research Project under Grant JCYJ20220531103008018 and Grant 20200812112423002in part by the Guangdong Basic Research Program under Grant 2019A1515110358,2021A1515012097in part by the open research fund of National Mobile Communications Research Laboratory,Southeast University (No.2021D16)。
文摘In this paper,we investigate the application of the Unmanned Aerial Vehicle(UAV)-enabled relaying system in emergency communications,where one UAV is applied as a relay to help transmit information from ground users to a Base Station(BS).We maximize the total transmitted data from the users to the BS,by optimizing the user communication scheduling and association along with the power allocation and the trajectory of the UAV.To solve this non-convex optimization problem,we propose the traditional Convex Optimization(CO)and the Reinforcement Learning(RL)-based approaches.Specifically,we apply the block coordinate descent and successive convex approximation techniques in the CO approach,while applying the soft actor-critic algorithm in the RL approach.The simulation results show that both approaches can solve the proposed optimization problem and obtain good results.Moreover,the RL approach establishes emergency communications more rapidly than the CO approach once the training process has been completed.
基金Doctoral Research Start-up Fund of Shandong Jiaotong University,Grant/Award Number:BS2024009Natural Science Foundation of Shandong Province of China,Grant/Award Number:ZR2022ME087+1 种基金State Key Laboratory of Robotics and Systems(HIT),Grant/Award Number:SKLRS-2024-KF-09Open Access Publication Fund of Universität Hamburg。
文摘Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment.With the aim to conveniently and accurately segment demonstration trajectories,a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model(BP-ARHMM)algorithm and generalised time warping(GTW)algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data.This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task.Then,it adopts the BP-AR-HMM algorithm to segment the demonstration trajectories,acquire the contained motion primitives,and establish the related task library.This segmentation approach is validated on the 6-degree-of-freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task.The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy.
基金supported by the Hunan Provin〓〓cial Natural Science Foundation for Excellent Young Scholars(Grant No.2023JJ20045)the National Natural Science Foundation of China(Grant No.12372189)。
文摘Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.
基金supported in part by the National Science Foundation of China(Grant No.62172450)the Key R&D Plan of Hunan Province(Grant No.2022GK2008)the Nature Science Foundation of Hunan Province(Grant No.2020JJ4756)。
文摘In task offloading,the movement of vehicles causes the switching of connected RSUs and servers,which may lead to task offloading failure or high service delay.In this paper,we analyze the impact of vehicle movements on task offloading and reveal that data preparation time for task execution can be minimized via forward-looking scheduling.Then,a Bi-LSTM-based model is proposed to predict the trajectories of vehicles.The service area is divided into several equal-sized grids.If the actual position of the vehicle and the predicted position by the model belong to the same grid,the prediction is considered correct,thereby reducing the difficulty of vehicle trajectory prediction.Moreover,we propose a scheduling strategy for delay optimization based on the vehicle trajectory prediction.Considering the inevitable prediction error,we take some edge servers around the predicted area as candidate execution servers and the data required for task execution are backed up to these candidate servers,thereby reducing the impact of prediction deviations on task offloading and converting the modest increase of resource overheads into delay reduction in task offloading.Simulation results show that,compared with other classical schemes,the proposed strategy has lower average task offloading delays.
基金Project supported by the National Natural Science Foundation of China(Grant No.12461047)the Scientific Research Project of the Hunan Education Department(Grant No.24B0478).
文摘Based on a new bilinear equation,we investigated some new dynamic behaviors of the(2+1)-dimensional shallow water wave model,such as hybridization behavior between different solitons,trajectory equations for lump collisions,and evolution behavior of multi-breathers.Firstly,the N-soliton solution of Ito equation is studied,and some high-order breather waves can be obtained from the N-soliton solutions through paired-complexification of parameters.Secondly,the high-order lump solutions and the hybrid solutions are obtained by employing the long-wave limit method,and the motion velocity and trajectory equations of high-order lump waves are analyzed.Moreover,based on the trajectory equations of the higher-order lump solutions,we give and prove the trajectory theorem of 1-lump before and after interaction with nsoliton.Finally,we obtain some new lump solutions from the multi-solitons by constructing a new test function and using the parameter limit method.Meanwhile,some evolutionary behaviors of the obtained solutions are shown through a large number of three-dimensional graphs with different and appropriate parameters.
基金supported by Project funded in part by China Postdoctoral Science Foundation(No.2021MD703980)in part by the National Natural Science Foundation of China(No.61901502).
文摘Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.
基金funded by the National Defense Science and Technology Innovation project,grant number ZZKY20223103the Basic Frontier InnovationProject at the Engineering University of PAP,grant number WJY202429+2 种基金the Basic Frontier lnnovation Project at the Engineering University of PAP,grant number WJY202408the Graduate Student Funding Priority Project,grant number JYWJ2024B006Key project of National Social Science Foundation,grant number 2023-SKJJ-A-116.
文摘This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.
