This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only b...This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.展开更多
A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source di...A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Developing intelligent unmanned swarm systems(IUSSs)is a highly intricate process.Although current simulators and toolchains have made a notable contribution to the develop-ment of algorithms for IUSSs,they tend to co...Developing intelligent unmanned swarm systems(IUSSs)is a highly intricate process.Although current simulators and toolchains have made a notable contribution to the develop-ment of algorithms for IUSSs,they tend to concentrate on iso-lated technical elements and are deficient in addressing the full spectrum of critical technologies and development needs in a systematic and integrative manner.Furthermore,the current suite of tools has not adequately addressed the challenge of bridging the gap between simulation and real-world deployment of algorithms.Therefore,a comprehensive solution must be developed that encompasses the entire IUSS development life-cycle.In this study,we present the RflySim ToolChain,which has been developed with the specific aim of facilitating the rapid development and validation of IUSSs.The RflySim ToolChain employs a model-based design(MBD)approach,integrating a modeling and simulation module,a lower reliable control mo-dule,and an upper swarm decision-making module.This compre-hensive integration encompasses the entire process,from mo-deling and simulation to testing and deployment,thereby enabling users to rapidly construct and validate IUSSs.The prin-cipal advantages of the RflySim ToolChain are as follows:it pro-vides a comprehensive solution that meets the full-stack devel-opment needs of IUSSs;the highly modular architecture and comprehensive software development kit(SDK)facilitate the automation of the entire IUSS development process.Further-more,the high-fidelity model design and reliable architecture solution ensure a seamless transition from simulation to real-world deployment,which is known as the simulation to reality(Sim2Real)process.This paper presents a series of case stu-dies that illustrate the effectiveness of the RflySim ToolChain in supporting the research and application of IUSSs.展开更多
The use of unmanned aerial system(UAS)in congested airspace and/or in the proximity of critical infrastructure poses several challenges as far as safe and secure operations are concerned.The paper provides a detailed ...The use of unmanned aerial system(UAS)in congested airspace and/or in the proximity of critical infrastructure poses several challenges as far as safe and secure operations are concerned.The paper provides a detailed description of the architecture and workflow of a platform for UAS traffic management(UTM),designed to pave the way for increased,improved and safer UAS operations in the civil airspace.In particular,access to low-altitude airspace for UAS operations is managed,while facilitating the implementation of beyond visual line-of-sight(BVLOS)operations,and ensuring a safe and efficient integration of UAS into both controlled and uncontrolled airspace.Detection and management of unidentified or uncooperative UAS’s is also taken care of.To this end,an architecture based on three interacting layers is proposed,with the air traffic control at the highest level,the UAS operator(s)at the bottom,and a UAS service supplier acting as an interface.The platform,with its physical and digital elements,guarantees the effective and efficient interaction among these three layers,including management of contingency scenarios,which require a variation of admissible flight volumes for UAS operations and/or fast trajectory re-planning.The platform,developed within a research project which involved several partners,was tested in a relevant operational scenario at the Grottaglie-Taranto airport in Italy.The operators involved in the tests provided positive feedback on the services provided by the platform and the usability of the interfaces,while also making suggestions for adding new features in future developments.展开更多
The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and p...The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.展开更多
Unmanned surface vehicles(USVs)play a crucial role in various fields,including ocean climate change monitoring,ma-rine resource exploitation,and ecological environment exploration.Out of the many types of USVs,unmanne...Unmanned surface vehicles(USVs)play a crucial role in various fields,including ocean climate change monitoring,ma-rine resource exploitation,and ecological environment exploration.Out of the many types of USVs,unmanned sailboats have gained considerable attention for their ability to conduct green,large-scale ocean observations.Building on this concept,this paper proposes an unmanned sailboat propelled by parallel dual-wing sails,which is designed to meet the demands of extensive and three-dimensional marine comprehensive observation and data collection.With a focus on the parallel dual-wing sails,this study particularly investi-gates the effects of variations in the airfoil’s angle of attack and the impact of the spacing ratio between the dual sails on propulsion performance.It further analyzes the influence of one sail’s angle of attack on the performance of the other sail,as well as the flow field between the two sails.For the air navigation and underwater states,the force characteristics of the dual sail under different inflow velocities were investigated.The research findings indicate that,under certain conditions,the thrust coefficient exhibits a trend of first increasing,then decreasing,and finally increasing again with alterations in the angle of attackα.Different single-sail angles of attack have varying impacts on the opposite sail and the flow field between the dual sails.Moreover,the generated forces are positively correlated with inflow velocity in the air navigation and underwater states.The findings reveal that it is possible to reduce drag,mitigate the adverse effects of sail interaction,and thereby enhance the propulsion performance and overall navigational stability of the sailboat by applying an optimal spacing ratio design and adjusting the angle of attack and inflow velocity.展开更多
This paper investigates the power generation characteristics of solar cells mounted on unmanned aerial vehicles(UAVs)under the coupled influence of flight conditions and the sur-rounding environment.Firstly,the study ...This paper investigates the power generation characteristics of solar cells mounted on unmanned aerial vehicles(UAVs)under the coupled influence of flight conditions and the sur-rounding environment.Firstly,the study reveals that the voltage,current,and power output of the solar cells undergo consistent temporal variations throughout the day,primarily driven by voltage fluctuations,with a peak occurring around noon.Secondly,it is observed that the cells’performance is significantly more influenced by temporal variations in external light intensity than by temperature changes resulting from variations in flight speed.Finally,the study finds that the impact of flight altitude on the cells’performance is slightly more pronounced than the influence of temporal variations in external light intensity.展开更多
When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution...When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.展开更多
As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UA...As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.展开更多
Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and miss...Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.展开更多
This study compared the control effect of 110 g/L etoxazole SC,15%abamectin·etoxazole SC,30%cyetpyrafen SC,43%bifenazate SC and 1.8%abamectin EC five acaricides sprayed by unmanned aerial vehicle(UAV)on Panonychu...This study compared the control effect of 110 g/L etoxazole SC,15%abamectin·etoxazole SC,30%cyetpyrafen SC,43%bifenazate SC and 1.8%abamectin EC five acaricides sprayed by unmanned aerial vehicle(UAV)on Panonychus citri,aiming to screen out the appropriate acaricide for the control of this pest by UAV spraying.The results showed that 15%abamectin·etoxazole SC and 30%cyetpyrafen SC had the highest control efficacy,which remained above 90%14 d after application.Secondary performance was observed in 43%bifenazate SC and 110 g/L etoxazole SC,which demonstrated enhancing control effect.However,1.8%abamectin EC showed slower effect.Considering the control effect and population reduction rate of P.citri,15%abamectin·etoxazole SC and 30%cyetpyrafen SC were suggested as the effective acaricides for the control of this pest.展开更多
A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on ...A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.展开更多
In response to the problems existing in the teaching of unmanned systems courses,such as being confined to traditional teaching models and insufficient focus on practical application,this paper proposes to guide the t...In response to the problems existing in the teaching of unmanned systems courses,such as being confined to traditional teaching models and insufficient focus on practical application,this paper proposes to guide the teaching with the OBE concept,carry out the teaching goal planning of unmanned systems application based on the OBE concept,innovate teaching methods,reconstruct course content,revitalize the teaching process,improve the evaluation model,and stimulate learning motivation to enhance the quality of course teaching and achieve the teaching goal of“knowledge+ability.”This has a certain reference value for the reform practice of unmanned systems courses.展开更多
Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data collection.Path planning of UAV advancing along river valleys in wild environments is one of the first and mos...Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data collection.Path planning of UAV advancing along river valleys in wild environments is one of the first and most difficult problems faced by unmanned surveys of debris flow valleys.This study proposes a new hybrid bat optimization algorithm,GRE-Bat(Good point set,Reverse learning,Elite Pool-Bat algorithm),for unmanned exploration path planning of debris flow sources in outdoor environments.In the GRE-Bat algorithm,the good point set strategy is adopted to evenly distribute the population,ensure sufficient coverage of the search space,and improve the stability of the convergence accuracy of the algorithm.Subsequently,a reverse learning strategy is introduced to increase the diversity of the population and improve the local stagnation problem of the algorithm.In addition,an Elite pool strategy is added to balance the replacement and learning behaviors of particles within the population based on elimination and local perturbation factors.To demonstrate the effectiveness of the GRE-Bat algorithm,we conducted multiple simulation experiments using benchmark test functions and digital terrain models.Compared to commonly used path planning algorithms such as the Bat Algorithm(BA)and the Improved Sparrow Search Algorithm(ISSA),the GRE-Bat algorithm can converge to the optimal value in different types of test functions and obtains a near-optimal solution after an average of 60 iterations.The GRE-Bat algorithm can obtain higher quality flight routes in the designated environment of unmanned investigation in the debris flow gully basin,demonstrating its potential for practical application.展开更多
As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilienc...As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.展开更多
The aperture of natural rock fractures significantly affects the deformation and strength properties of rock masses,as well as the hydrodynamic properties of fractured rock masses.The conventional measurement methods ...The aperture of natural rock fractures significantly affects the deformation and strength properties of rock masses,as well as the hydrodynamic properties of fractured rock masses.The conventional measurement methods are inadequate for collecting data on high-steep rock slopes in complex mountainous regions.This study establishes a high-resolution three-dimensional model of a rock slope using unmanned aerial vehicle(UAV)multi-angle nap-of-the-object photogrammetry to obtain edge feature points of fractures.Fracture opening morphology is characterized using coordinate projection and transformation.Fracture central axis is determined using vertical measuring lines,allowing for the interpretation of aperture of adaptive fracture shape.The feasibility and reliability of the new method are verified at a construction site of a railway in southeast Xizang,China.The study shows that the fracture aperture has a significant interval effect and size effect.The optimal sampling length for fractures is approximately 0.5e1 m,and the optimal aperture interpretation results can be achieved when the measuring line spacing is 1%of the sampling length.Tensile fractures in the study area generally have larger apertures than shear fractures,and their tendency to increase with slope height is also greater than that of shear fractures.The aperture of tensile fractures is generally positively correlated with their trace length,while the correlation between the aperture of shear fractures and their trace length appears to be weak.Fractures of different orientations exhibit certain differences in their distribution of aperture,but generally follow the forms of normal,log-normal,and gamma distributions.This study provides essential data support for rock and slope stability evaluation,which is of significant practical importance.展开更多
Unmanned autonomous Air-to-Air Refueling(AAR)capability is the key guarantee to support the distant-field,high-intensity and durable operations of the penetration counterair combat system.In the future,the long-range ...Unmanned autonomous Air-to-Air Refueling(AAR)capability is the key guarantee to support the distant-field,high-intensity and durable operations of the penetration counterair combat system.In the future,the long-range unmanned reconnaissance and attack platform can reach the maximum flight range requirement through AAR.At present,large transport aircraft platforms in China are still equipped with probe-and-drogue systems,and the refueling mode is gradually changing from manned to unmanned autonomous operation.The docking process is the riskiest and most important part,and there are strict safety,precision,and efficiency requirements for refueling operation,especially during close-distance docking and formation maintenance phases.In this paper,five issues that need to be solved to achieve autonomous AAR docking are summarized.On this basis,five key technology development needs are proposed to solve these engineering issues.Finally,some prospects are given.展开更多
Efficient and high-quality estimation of key phenological dates in rice is of great significance in breeding work. Plant height(PH) dynamics are valuable for estimating phenological dates. However, research on estimat...Efficient and high-quality estimation of key phenological dates in rice is of great significance in breeding work. Plant height(PH) dynamics are valuable for estimating phenological dates. However, research on estimating the key phenological dates of multiple rice accessions based on PH dynamics has been limited. In 2022, field traits were collected using unmanned aerial vehicle(UAV)-based images across 435 plots, including 364 rice varieties. PH, dates of initial heading(IH) and full heading(FH), and panicle initiation(PI), and growth period after transplanting(GPAT) were collected during the rice growth stage. PHs were extracted using a digital surface model(DSM) and fitted using Fourier and logistic models. Machine learning algorithms, including multiple linear regression, random forest(RF), support vector regression, least absolute shrinkage and selection operator, and elastic net regression, were employed to estimate phenological dates. Results indicated that the optimal percentile of the DSM for extracting rice PH was the 95th(R^(2) = 0.934, RMSE = 0.056 m). The Fourier model provided a better fit for PH dynamics compared with the logistic models. Additionally, curve features(CF) and GPAT were significantly associated with PI, IH, and FH. The combination of CF and GPAT outperformed the use of CF alone, with RF demonstrating the best performance among the algorithms. Specifically, the combination of CF extracted from the logistic models, GPAT, and RF yielded the best performance for estimating PI(R^(2) = 0.834, RMSE = 4.344 d), IH(R^(2) = 0.877, RMSE = 2.721 d), and FH(R^(2) = 0.883, RMSE = 2.694 d). Overall, UAV-based rice PH dynamics combined with machine learning effectively estimated the key phenological dates of multiple rice accessions, providing a novel approach for investigating key phenological dates in breeding work.展开更多
Controlled and switchable adhesion is commonly observed in biological systems.In recent years,many scholars have focused on making switchable bio-inspired adhesives.However,making a bio-inspired adhesive with high adh...Controlled and switchable adhesion is commonly observed in biological systems.In recent years,many scholars have focused on making switchable bio-inspired adhesives.However,making a bio-inspired adhesive with high adhesion performance and excellent dynamic switching properties is still a challenge.A Shape Memory Polymer Bio-inspired Adhesive(SMPBA)was successfully developed,well realizing high adhesion(about 337 kPa),relatively low preload(about90 kPa),high adhesion-to-preload ratio(about 3.74),high switching ratio(about 6.74),and easy detachment,which are attributed to the controlled modulus and contact area by regulating temperature and the Shape Memory Effect(SME).Furthermore,SMPBA exhibits adhesion strength of80–337 kPa on various surfaces(silicon,iron,and aluminum)with different roughness(Ra=0.021–10.280)because of the conformal contact,reflecting outstanding surface adaptability.The finite element analysis verifies the bending ability under different temperatures,while the adhesion model analyzes the influence of preload on contact area and adhesion.Furthermore,an Unmanned Aerial Vehicle(UAV)landing device with SMPBA was designed and manufactured to achieve UAV landing on and detaching from various surfaces.This study provides a novel switchable bio-inspired adhesive and UAV landing method.展开更多
文摘This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.
基金co-supported by the National Key R&D Program of China(No.2023YFB4704400)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F030012)the National Natural Science Foundation of China General Project(No.62373033)。
文摘A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金supported by the National Natural Science Foundation of China(62406345).
文摘Developing intelligent unmanned swarm systems(IUSSs)is a highly intricate process.Although current simulators and toolchains have made a notable contribution to the develop-ment of algorithms for IUSSs,they tend to concentrate on iso-lated technical elements and are deficient in addressing the full spectrum of critical technologies and development needs in a systematic and integrative manner.Furthermore,the current suite of tools has not adequately addressed the challenge of bridging the gap between simulation and real-world deployment of algorithms.Therefore,a comprehensive solution must be developed that encompasses the entire IUSS development life-cycle.In this study,we present the RflySim ToolChain,which has been developed with the specific aim of facilitating the rapid development and validation of IUSSs.The RflySim ToolChain employs a model-based design(MBD)approach,integrating a modeling and simulation module,a lower reliable control mo-dule,and an upper swarm decision-making module.This compre-hensive integration encompasses the entire process,from mo-deling and simulation to testing and deployment,thereby enabling users to rapidly construct and validate IUSSs.The prin-cipal advantages of the RflySim ToolChain are as follows:it pro-vides a comprehensive solution that meets the full-stack devel-opment needs of IUSSs;the highly modular architecture and comprehensive software development kit(SDK)facilitate the automation of the entire IUSS development process.Further-more,the high-fidelity model design and reliable architecture solution ensure a seamless transition from simulation to real-world deployment,which is known as the simulation to reality(Sim2Real)process.This paper presents a series of case stu-dies that illustrate the effectiveness of the RflySim ToolChain in supporting the research and application of IUSSs.
基金supported by the European Union and Italian Ministry of University and Research through the call PON Research and Innovation 2014-2020,Axis Ⅱ,Action 2,project AcrOSS(Environment for Safe Operations of Remotely Piloted Aircraft),project number ARS01_00702-CUP:F36C18000210005.
文摘The use of unmanned aerial system(UAS)in congested airspace and/or in the proximity of critical infrastructure poses several challenges as far as safe and secure operations are concerned.The paper provides a detailed description of the architecture and workflow of a platform for UAS traffic management(UTM),designed to pave the way for increased,improved and safer UAS operations in the civil airspace.In particular,access to low-altitude airspace for UAS operations is managed,while facilitating the implementation of beyond visual line-of-sight(BVLOS)operations,and ensuring a safe and efficient integration of UAS into both controlled and uncontrolled airspace.Detection and management of unidentified or uncooperative UAS’s is also taken care of.To this end,an architecture based on three interacting layers is proposed,with the air traffic control at the highest level,the UAS operator(s)at the bottom,and a UAS service supplier acting as an interface.The platform,with its physical and digital elements,guarantees the effective and efficient interaction among these three layers,including management of contingency scenarios,which require a variation of admissible flight volumes for UAS operations and/or fast trajectory re-planning.The platform,developed within a research project which involved several partners,was tested in a relevant operational scenario at the Grottaglie-Taranto airport in Italy.The operators involved in the tests provided positive feedback on the services provided by the platform and the usability of the interfaces,while also making suggestions for adding new features in future developments.
基金supported by the National Natural Science Foundation of China(U20B2042).
文摘The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.
基金supported from the Shandong Provincial Natural Science Foundation(No.ZR2022ME147)the National Natural Science Foundation of China(No.52088102).
文摘Unmanned surface vehicles(USVs)play a crucial role in various fields,including ocean climate change monitoring,ma-rine resource exploitation,and ecological environment exploration.Out of the many types of USVs,unmanned sailboats have gained considerable attention for their ability to conduct green,large-scale ocean observations.Building on this concept,this paper proposes an unmanned sailboat propelled by parallel dual-wing sails,which is designed to meet the demands of extensive and three-dimensional marine comprehensive observation and data collection.With a focus on the parallel dual-wing sails,this study particularly investi-gates the effects of variations in the airfoil’s angle of attack and the impact of the spacing ratio between the dual sails on propulsion performance.It further analyzes the influence of one sail’s angle of attack on the performance of the other sail,as well as the flow field between the two sails.For the air navigation and underwater states,the force characteristics of the dual sail under different inflow velocities were investigated.The research findings indicate that,under certain conditions,the thrust coefficient exhibits a trend of first increasing,then decreasing,and finally increasing again with alterations in the angle of attackα.Different single-sail angles of attack have varying impacts on the opposite sail and the flow field between the dual sails.Moreover,the generated forces are positively correlated with inflow velocity in the air navigation and underwater states.The findings reveal that it is possible to reduce drag,mitigate the adverse effects of sail interaction,and thereby enhance the propulsion performance and overall navigational stability of the sailboat by applying an optimal spacing ratio design and adjusting the angle of attack and inflow velocity.
基金supported by the National Natural Science Foundation of China(Nos.12464010,52462035)2022 Jiangxi Province High-Level and High-Skilled Leading Talent Training Project Selected(No.63)+1 种基金Jiujiang“Xuncheng Talents”(No.JJXC2023032)Jiujiang Basic Research Program Project(2025).
文摘This paper investigates the power generation characteristics of solar cells mounted on unmanned aerial vehicles(UAVs)under the coupled influence of flight conditions and the sur-rounding environment.Firstly,the study reveals that the voltage,current,and power output of the solar cells undergo consistent temporal variations throughout the day,primarily driven by voltage fluctuations,with a peak occurring around noon.Secondly,it is observed that the cells’performance is significantly more influenced by temporal variations in external light intensity than by temperature changes resulting from variations in flight speed.Finally,the study finds that the impact of flight altitude on the cells’performance is slightly more pronounced than the influence of temporal variations in external light intensity.
基金supported by the National Natural Science Foundation of China(72471240).
文摘When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.
基金supported by the National Natural Science Foundation of China (No. 62073267)。
文摘As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.
文摘Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.
文摘This study compared the control effect of 110 g/L etoxazole SC,15%abamectin·etoxazole SC,30%cyetpyrafen SC,43%bifenazate SC and 1.8%abamectin EC five acaricides sprayed by unmanned aerial vehicle(UAV)on Panonychus citri,aiming to screen out the appropriate acaricide for the control of this pest by UAV spraying.The results showed that 15%abamectin·etoxazole SC and 30%cyetpyrafen SC had the highest control efficacy,which remained above 90%14 d after application.Secondary performance was observed in 43%bifenazate SC and 110 g/L etoxazole SC,which demonstrated enhancing control effect.However,1.8%abamectin EC showed slower effect.Considering the control effect and population reduction rate of P.citri,15%abamectin·etoxazole SC and 30%cyetpyrafen SC were suggested as the effective acaricides for the control of this pest.
文摘A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.
文摘In response to the problems existing in the teaching of unmanned systems courses,such as being confined to traditional teaching models and insufficient focus on practical application,this paper proposes to guide the teaching with the OBE concept,carry out the teaching goal planning of unmanned systems application based on the OBE concept,innovate teaching methods,reconstruct course content,revitalize the teaching process,improve the evaluation model,and stimulate learning motivation to enhance the quality of course teaching and achieve the teaching goal of“knowledge+ability.”This has a certain reference value for the reform practice of unmanned systems courses.
基金supported by National Natural Science Foundation of China(No.42302336)Project of the Department of Science and Technology of Sichuan Province(No.2024YFHZ0098,No.2023NSFSC0751)Open Project of Chengdu University of Information Technology(KYQN202317,760115027,KYTZ202278,KYTZ202280).
文摘Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data collection.Path planning of UAV advancing along river valleys in wild environments is one of the first and most difficult problems faced by unmanned surveys of debris flow valleys.This study proposes a new hybrid bat optimization algorithm,GRE-Bat(Good point set,Reverse learning,Elite Pool-Bat algorithm),for unmanned exploration path planning of debris flow sources in outdoor environments.In the GRE-Bat algorithm,the good point set strategy is adopted to evenly distribute the population,ensure sufficient coverage of the search space,and improve the stability of the convergence accuracy of the algorithm.Subsequently,a reverse learning strategy is introduced to increase the diversity of the population and improve the local stagnation problem of the algorithm.In addition,an Elite pool strategy is added to balance the replacement and learning behaviors of particles within the population based on elimination and local perturbation factors.To demonstrate the effectiveness of the GRE-Bat algorithm,we conducted multiple simulation experiments using benchmark test functions and digital terrain models.Compared to commonly used path planning algorithms such as the Bat Algorithm(BA)and the Improved Sparrow Search Algorithm(ISSA),the GRE-Bat algorithm can converge to the optimal value in different types of test functions and obtains a near-optimal solution after an average of 60 iterations.The GRE-Bat algorithm can obtain higher quality flight routes in the designated environment of unmanned investigation in the debris flow gully basin,demonstrating its potential for practical application.
基金This work was supported by Ph.D.Intelligent Innovation Foundation Project(201-CXCY-A01-08-19-01)Science and Technology on Information System Engineering Laboratory(05202007).
文摘As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.
基金supported by the National Nature Science Foundation of China(Grant Nos.42177139 and 41941017)the Natural Science Foundation Project of Jilin Province,China(Grant No.20230101088JC).The authors would like to thank the anonymous reviewers for their comments and suggestions.
文摘The aperture of natural rock fractures significantly affects the deformation and strength properties of rock masses,as well as the hydrodynamic properties of fractured rock masses.The conventional measurement methods are inadequate for collecting data on high-steep rock slopes in complex mountainous regions.This study establishes a high-resolution three-dimensional model of a rock slope using unmanned aerial vehicle(UAV)multi-angle nap-of-the-object photogrammetry to obtain edge feature points of fractures.Fracture opening morphology is characterized using coordinate projection and transformation.Fracture central axis is determined using vertical measuring lines,allowing for the interpretation of aperture of adaptive fracture shape.The feasibility and reliability of the new method are verified at a construction site of a railway in southeast Xizang,China.The study shows that the fracture aperture has a significant interval effect and size effect.The optimal sampling length for fractures is approximately 0.5e1 m,and the optimal aperture interpretation results can be achieved when the measuring line spacing is 1%of the sampling length.Tensile fractures in the study area generally have larger apertures than shear fractures,and their tendency to increase with slope height is also greater than that of shear fractures.The aperture of tensile fractures is generally positively correlated with their trace length,while the correlation between the aperture of shear fractures and their trace length appears to be weak.Fractures of different orientations exhibit certain differences in their distribution of aperture,but generally follow the forms of normal,log-normal,and gamma distributions.This study provides essential data support for rock and slope stability evaluation,which is of significant practical importance.
文摘Unmanned autonomous Air-to-Air Refueling(AAR)capability is the key guarantee to support the distant-field,high-intensity and durable operations of the penetration counterair combat system.In the future,the long-range unmanned reconnaissance and attack platform can reach the maximum flight range requirement through AAR.At present,large transport aircraft platforms in China are still equipped with probe-and-drogue systems,and the refueling mode is gradually changing from manned to unmanned autonomous operation.The docking process is the riskiest and most important part,and there are strict safety,precision,and efficiency requirements for refueling operation,especially during close-distance docking and formation maintenance phases.In this paper,five issues that need to be solved to achieve autonomous AAR docking are summarized.On this basis,five key technology development needs are proposed to solve these engineering issues.Finally,some prospects are given.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFD2300700)the Open Project Program of the State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute (Grant No.2023ZZKT20402)+1 种基金the Agricultural Science and Technology Innovation Program, the Central Public-Interest Scientific Institution Basal Research Fund, China (Grant No.CPSIBRF-CNRRI-202119)the Zhejiang ‘Ten Thousand Talents’ Plan Science and Technology Innovation Leading Talent Project, China (Grant No.2020R52035)。
文摘Efficient and high-quality estimation of key phenological dates in rice is of great significance in breeding work. Plant height(PH) dynamics are valuable for estimating phenological dates. However, research on estimating the key phenological dates of multiple rice accessions based on PH dynamics has been limited. In 2022, field traits were collected using unmanned aerial vehicle(UAV)-based images across 435 plots, including 364 rice varieties. PH, dates of initial heading(IH) and full heading(FH), and panicle initiation(PI), and growth period after transplanting(GPAT) were collected during the rice growth stage. PHs were extracted using a digital surface model(DSM) and fitted using Fourier and logistic models. Machine learning algorithms, including multiple linear regression, random forest(RF), support vector regression, least absolute shrinkage and selection operator, and elastic net regression, were employed to estimate phenological dates. Results indicated that the optimal percentile of the DSM for extracting rice PH was the 95th(R^(2) = 0.934, RMSE = 0.056 m). The Fourier model provided a better fit for PH dynamics compared with the logistic models. Additionally, curve features(CF) and GPAT were significantly associated with PI, IH, and FH. The combination of CF and GPAT outperformed the use of CF alone, with RF demonstrating the best performance among the algorithms. Specifically, the combination of CF extracted from the logistic models, GPAT, and RF yielded the best performance for estimating PI(R^(2) = 0.834, RMSE = 4.344 d), IH(R^(2) = 0.877, RMSE = 2.721 d), and FH(R^(2) = 0.883, RMSE = 2.694 d). Overall, UAV-based rice PH dynamics combined with machine learning effectively estimated the key phenological dates of multiple rice accessions, providing a novel approach for investigating key phenological dates in breeding work.
基金financial support from the National Natural Science Foundation of China(No.51605220)the Jiangsu Province Natural Science Foundation,China(No.BK20160793)+1 种基金the Postgraduate Research and Practice Innovation Program of Nanjing University of Aeronautics and Astronautics,China(No.xcxjh20210514)the Fundamental Research Funds for the Central Universities,China(No.XCA2205406)。
文摘Controlled and switchable adhesion is commonly observed in biological systems.In recent years,many scholars have focused on making switchable bio-inspired adhesives.However,making a bio-inspired adhesive with high adhesion performance and excellent dynamic switching properties is still a challenge.A Shape Memory Polymer Bio-inspired Adhesive(SMPBA)was successfully developed,well realizing high adhesion(about 337 kPa),relatively low preload(about90 kPa),high adhesion-to-preload ratio(about 3.74),high switching ratio(about 6.74),and easy detachment,which are attributed to the controlled modulus and contact area by regulating temperature and the Shape Memory Effect(SME).Furthermore,SMPBA exhibits adhesion strength of80–337 kPa on various surfaces(silicon,iron,and aluminum)with different roughness(Ra=0.021–10.280)because of the conformal contact,reflecting outstanding surface adaptability.The finite element analysis verifies the bending ability under different temperatures,while the adhesion model analyzes the influence of preload on contact area and adhesion.Furthermore,an Unmanned Aerial Vehicle(UAV)landing device with SMPBA was designed and manufactured to achieve UAV landing on and detaching from various surfaces.This study provides a novel switchable bio-inspired adhesive and UAV landing method.
