Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Un...Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.展开更多
The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicl...The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective- ness of the orooosed aooroach.展开更多
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
Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunatel...Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.展开更多
Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees l...Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.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
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
Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptibl...Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptible to security and privacy threats due to hardware and architectural issues. Although small drones hold promise for expansion in both civil and defense sectors, they have safety, security, and privacy threats. Addressing these challenges is crucial to maintaining the security and uninterrupted operations of these drones. In this regard, this study investigates security, and preservation concerning both the drones and Internet of Drones (IoD), emphasizing the significance of creating drone networks that are secure and can robustly withstand interceptions and intrusions. The proposed framework incorporates a weighted voting ensemble model comprising three convolutional neural network (CNN) models to enhance intrusion detection within the network. The employed CNNs are customized 1D models optimized to obtain better performance. The output from these CNNs is voted using a weighted criterion using a 0.4, 0.3, and 0.3 ratio for three CNNs, respectively. Experiments involve using multiple benchmark datasets, achieving an impressive accuracy of up to 99.89% on drone data. The proposed model shows promising results concerning precision, recall, and F1 as indicated by their obtained values of 99.92%, 99.98%, and 99.97%, respectively. Furthermore, cross-validation and performance comparison with existing works is also carried out. Findings indicate that the proposed approach offers a prospective solution for detecting security threats for aerial systems and satellite systems with high accuracy.展开更多
In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone ...In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.展开更多
This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault...This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.展开更多
Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site mapping.Utilizing UAVs to assist communications is one of the promising applications and rese...Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site mapping.Utilizing UAVs to assist communications is one of the promising applications and research directions.The future Industrial Internet places higher demands on communication quality.The easy deployment,dynamic mobility,and low cost of UAVs make them a viable tool for wireless communication in the Industrial Internet.Therefore,UAVs are considered as an integral part of Industry 4.0.In this article,three typical use cases of UAVs-assisted communications in Industrial Internet are first summarized.Then,the state-of-the-art technologies for drone-assisted communication in support of the Industrial Internet are presented.According to the current research,it can be assumed that UAV-assisted communication can support the future Industrial Internet to a certain extent.Finally,the potential research directions and open challenges in UAV-assisted communications in the upcoming future Industrial Internet are discussed.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
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
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
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
As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational ...As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.展开更多
To achieve the track following and collision avoidance of underactuated unmanned surface vehicle(USV),autonomous navigation model based on model predictive control is established by including the track offset,speed va...To achieve the track following and collision avoidance of underactuated unmanned surface vehicle(USV),autonomous navigation model based on model predictive control is established by including the track offset,speed variation and rule compliance as the evaluation functions and including the ship domain of dynamic/static navigation obstacles and the mechanical characteristics limitation as constraints.The effectiveness of the model for autonomous navigation of USV in the situation of multi-ship encounters and in the complex waters with both dynamic and static obstructions is verified by several groups of simulation work.The simulation results show that the proposed model can realize the autonomous navigation of the underactuated USV under the complex waters.展开更多
Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resour...Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resource allocation method for unmanned aerial vehicle(UAV)-assisted and user cooperation non-linear energy harvesting mobile edge computing(MEC)system is proposed.The UAV equipped with an MEC server is introduced to provide energy and computing services for the remote user group to alleviate the doubly near-far problem in a large range suffered by the remote user group.The doubly near-far problem in a small range existing in both nearby and remote user groups is mitigated by user cooperation.The specific user cooperation strategy is that the user near the base station or the UAV is used as a relay to transfer the computing task of the user far from the base station or the UAV to the MEC server for computing.By jointly optimizing users’offloading time,users’transmitting power,and the hovering position of the UAV,the resource allocation problem is modeled as a nonlinear programming problem with the objective of maximizing computation efficiency.The suboptimal solution is obtained by adopting the differential evolution algorithm.Simulation results show that,compared with the resource allocation method based on genetic algorithm and the without user cooperation method,the proposed method has higher computation efficiency.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
基金This work was funded by the research center of the Future University in Egypt,in 2023.
文摘Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.
基金supported by National Natural Science Foundation of China (No.61074027)National Defense Pre-research Foundation of China (No.9140C48020212HK0101)
文摘The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective- ness of the orooosed aooroach.
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.
文摘Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.
基金supported in part by 14th Five Year National Key R&D Program Project(Project Number:2023YFB3211001)the National Natural Science Foundation of China(62273339,U24A201397).
文摘Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.
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Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptible to security and privacy threats due to hardware and architectural issues. Although small drones hold promise for expansion in both civil and defense sectors, they have safety, security, and privacy threats. Addressing these challenges is crucial to maintaining the security and uninterrupted operations of these drones. In this regard, this study investigates security, and preservation concerning both the drones and Internet of Drones (IoD), emphasizing the significance of creating drone networks that are secure and can robustly withstand interceptions and intrusions. The proposed framework incorporates a weighted voting ensemble model comprising three convolutional neural network (CNN) models to enhance intrusion detection within the network. The employed CNNs are customized 1D models optimized to obtain better performance. The output from these CNNs is voted using a weighted criterion using a 0.4, 0.3, and 0.3 ratio for three CNNs, respectively. Experiments involve using multiple benchmark datasets, achieving an impressive accuracy of up to 99.89% on drone data. The proposed model shows promising results concerning precision, recall, and F1 as indicated by their obtained values of 99.92%, 99.98%, and 99.97%, respectively. Furthermore, cross-validation and performance comparison with existing works is also carried out. Findings indicate that the proposed approach offers a prospective solution for detecting security threats for aerial systems and satellite systems with high accuracy.
基金This work was supported by the Postdoctoral Fund of FDCT,Macao(Grant No.0003/2021/APD).Any opinions,findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.
文摘In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.
基金the National Natural Science Foundation of China(62303012,62236002,61911004,62303008)。
文摘This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.
基金supported in part by National Key Research&Devel-opment Program of China(2021YFB2900801)in part by Guangdong Basic and Applied Basic Research Foundation(2022A1515110335)in party by Fundamental Research Funds for the Central Universities(FRF-TP-22-094A1).
文摘Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site mapping.Utilizing UAVs to assist communications is one of the promising applications and research directions.The future Industrial Internet places higher demands on communication quality.The easy deployment,dynamic mobility,and low cost of UAVs make them a viable tool for wireless communication in the Industrial Internet.Therefore,UAVs are considered as an integral part of Industry 4.0.In this article,three typical use cases of UAVs-assisted communications in Industrial Internet are first summarized.Then,the state-of-the-art technologies for drone-assisted communication in support of the Industrial Internet are presented.According to the current research,it can be assumed that UAV-assisted communication can support the future Industrial Internet to a certain extent.Finally,the potential research directions and open challenges in UAV-assisted communications in the upcoming future Industrial Internet are discussed.
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(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 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in part by the National Natural Science Foundation of China(NSFC)under Grant 62371012in part by the Beijing Natural Science Foundation under Grant 4252001.
文摘As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.
基金the National Natural Science Foundation of China(No.51879119)the Key Projects of National Key Research and Development Program(No.2021YFB390150)+1 种基金the Natural Science Project of Fujian Province(Nos.2022J01323,2021J01822 and 2020J01660)the Fuzhou-Xiamen-Quanzhou Independent Innovation Region Cooperated Special Foundation(No.3502ZCQXT2021007)。
文摘To achieve the track following and collision avoidance of underactuated unmanned surface vehicle(USV),autonomous navigation model based on model predictive control is established by including the track offset,speed variation and rule compliance as the evaluation functions and including the ship domain of dynamic/static navigation obstacles and the mechanical characteristics limitation as constraints.The effectiveness of the model for autonomous navigation of USV in the situation of multi-ship encounters and in the complex waters with both dynamic and static obstructions is verified by several groups of simulation work.The simulation results show that the proposed model can realize the autonomous navigation of the underactuated USV under the complex waters.
基金the National Natural Science Foundation of China(No.61871133)the Natural Science Foundation of Fujian Province(No.2021J01587)。
文摘Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resource allocation method for unmanned aerial vehicle(UAV)-assisted and user cooperation non-linear energy harvesting mobile edge computing(MEC)system is proposed.The UAV equipped with an MEC server is introduced to provide energy and computing services for the remote user group to alleviate the doubly near-far problem in a large range suffered by the remote user group.The doubly near-far problem in a small range existing in both nearby and remote user groups is mitigated by user cooperation.The specific user cooperation strategy is that the user near the base station or the UAV is used as a relay to transfer the computing task of the user far from the base station or the UAV to the MEC server for computing.By jointly optimizing users’offloading time,users’transmitting power,and the hovering position of the UAV,the resource allocation problem is modeled as a nonlinear programming problem with the objective of maximizing computation efficiency.The suboptimal solution is obtained by adopting the differential evolution algorithm.Simulation results show that,compared with the resource allocation method based on genetic algorithm and the without user cooperation method,the proposed method has higher computation efficiency.
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.
