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
The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such...The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such as path planning,situational awareness,and information transmission.Due to the openness of the network,the UAV cluster is more vulnerable to passive eavesdropping,active interference,and other attacks,which makes the system face serious security threats.This paper proposes a Blockchain-Based Data Acquisition(BDA)scheme with privacy protection to address the data privacy and identity authentication problems in the UAV-assisted data acquisition scenario.Each UAV cluster has an aggregate unmanned aerial vehicle(AGV)that can batch-verify the acquisition reports within its administrative domain.After successful verification,AGV adds its signcrypted ciphertext to the aggregation and uploads it to the blockchain for storage.There are two chains in the blockchain that store the public key information of registered entities and the aggregated reports,respectively.The security analysis shows that theBDAconstruction can protect the privacy and authenticity of acquisition data,and effectively resist a malicious key generation center and the public-key substitution attack.It also provides unforgeability to acquisition reports under the Elliptic Curve Discrete Logarithm Problem(ECDLP)assumption.The performance analysis demonstrates that compared with other schemes,the proposed BDA construction has lower computational complexity and is more suitable for the UAV cluster network with limited computing power and storage capacity.展开更多
Cooperative unmanned aerial vehicles(UAVs)cluster technology is considered a prospective solution for area coverage problems,enabling network access and emergency communications in remote areas.In this paper,we invest...Cooperative unmanned aerial vehicles(UAVs)cluster technology is considered a prospective solution for area coverage problems,enabling network access and emergency communications in remote areas.In this paper,we investigate how to control UAV cluster to achieve long-term and stable regional coverage while maintaining link connectivity and minimizing energy consumption,given the limited communication range and energy consumption of the UAVs themselves.To this end,we propose a cooperative UAV cluster strategy based on multi-agent deep reinforcement learning(MADRL)to achieve fair coverage of communication regions,which we call MADRL-based cooperative UAV cluster strategy(MADRL-CUCS).Our solution is a centralized training distributed execution architecture and defines a cluster structure for leader UAVs and follower UAVs.Under the premise of comprehensively considering the maximum coverage,we use a new energy efficiency function to minimize energy consumption,so as to extend the network lifetime of the UAVs cluster networks.The new fairness index and collision avoidance factor are used to ensure that the UAV cluster achieve effective and secure regional coverage.We adopt depth first search algorithm to check the link connectivity of the UAVs during the coverage process.Experiments show that the MADRL-CUCS algorithm outperforms the benchmark algorithm.展开更多
The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefi...The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefined configuration around the leader is considered as the objective.Unlike prior studies,the information of the central reference trajectory,which is deemed as a virtual leader in the leader-follower topology,is not directly accessible for partial nodes through the communication network.Therefore,a novel distributed formation tracking control scheme is promoted.Besides,a decentralized saturation observer is employed to estimate the reference acceleration signal of the virtual leader.In the absence of linear velocity measurement,two sliding manifolds are proposed by introducing the relative discrepancy terms of position and velocity.Then a smooth saturation operator in the form of a sigmoid function is applied to generate the command force input.Moreover,under the dilemma of constrained capabilities of the airborne sensors equipped on the rotorcrafts,the angular velocity is difficult to acquire.Two cascaded auxiliary attitude error systems are established on each rotorcraft system to synthesize the rotating torque with no need to require the angular velocity measurement.Due to the strong coupling and nonlinearity of the rotorcraft UAV system,the command angular velocity and the derivatives of command input are hard to obtain.Then a continuous nonlinear differentiator is proposed to work with the difficulties in deriving the explicit expression of system derivatives.Thereafter,a detailed stability analysis is conducted progressively on the angular control loop,reference trajectory observer loop,and the position control loop.A simulation scheme for a cluster of four rotorcraft UAVs tracking sinusoidal trajectory are presented and the formation control results are proven advantageous in comparison with the control protocol in previous literature.展开更多
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 in part by the National Key R&D Program of China under Project 2020YFB1006004the Guangxi Natural Science Foundation under Grants 2019GXNSFFA245015 and 2019GXNSFGA245004+2 种基金the National Natural Science Foundation of China under Projects 62162017,61862012,61962012,and 62172119the Major Key Project of PCL under Grants PCL2021A09,PCL2021A02 and PCL2022A03the Innovation Project of Guangxi Graduate Education YCSW2021175.
文摘The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such as path planning,situational awareness,and information transmission.Due to the openness of the network,the UAV cluster is more vulnerable to passive eavesdropping,active interference,and other attacks,which makes the system face serious security threats.This paper proposes a Blockchain-Based Data Acquisition(BDA)scheme with privacy protection to address the data privacy and identity authentication problems in the UAV-assisted data acquisition scenario.Each UAV cluster has an aggregate unmanned aerial vehicle(AGV)that can batch-verify the acquisition reports within its administrative domain.After successful verification,AGV adds its signcrypted ciphertext to the aggregation and uploads it to the blockchain for storage.There are two chains in the blockchain that store the public key information of registered entities and the aggregated reports,respectively.The security analysis shows that theBDAconstruction can protect the privacy and authenticity of acquisition data,and effectively resist a malicious key generation center and the public-key substitution attack.It also provides unforgeability to acquisition reports under the Elliptic Curve Discrete Logarithm Problem(ECDLP)assumption.The performance analysis demonstrates that compared with other schemes,the proposed BDA construction has lower computational complexity and is more suitable for the UAV cluster network with limited computing power and storage capacity.
基金supported by the National Natural Science Foundation of China(No.62376165).
文摘Cooperative unmanned aerial vehicles(UAVs)cluster technology is considered a prospective solution for area coverage problems,enabling network access and emergency communications in remote areas.In this paper,we investigate how to control UAV cluster to achieve long-term and stable regional coverage while maintaining link connectivity and minimizing energy consumption,given the limited communication range and energy consumption of the UAVs themselves.To this end,we propose a cooperative UAV cluster strategy based on multi-agent deep reinforcement learning(MADRL)to achieve fair coverage of communication regions,which we call MADRL-based cooperative UAV cluster strategy(MADRL-CUCS).Our solution is a centralized training distributed execution architecture and defines a cluster structure for leader UAVs and follower UAVs.Under the premise of comprehensively considering the maximum coverage,we use a new energy efficiency function to minimize energy consumption,so as to extend the network lifetime of the UAVs cluster networks.The new fairness index and collision avoidance factor are used to ensure that the UAV cluster achieve effective and secure regional coverage.We adopt depth first search algorithm to check the link connectivity of the UAVs during the coverage process.Experiments show that the MADRL-CUCS algorithm outperforms the benchmark algorithm.
基金supported by the National Natural Science Foundation of China(Grant Nos.62350048 and U20B2071)。
文摘The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefined configuration around the leader is considered as the objective.Unlike prior studies,the information of the central reference trajectory,which is deemed as a virtual leader in the leader-follower topology,is not directly accessible for partial nodes through the communication network.Therefore,a novel distributed formation tracking control scheme is promoted.Besides,a decentralized saturation observer is employed to estimate the reference acceleration signal of the virtual leader.In the absence of linear velocity measurement,two sliding manifolds are proposed by introducing the relative discrepancy terms of position and velocity.Then a smooth saturation operator in the form of a sigmoid function is applied to generate the command force input.Moreover,under the dilemma of constrained capabilities of the airborne sensors equipped on the rotorcrafts,the angular velocity is difficult to acquire.Two cascaded auxiliary attitude error systems are established on each rotorcraft system to synthesize the rotating torque with no need to require the angular velocity measurement.Due to the strong coupling and nonlinearity of the rotorcraft UAV system,the command angular velocity and the derivatives of command input are hard to obtain.Then a continuous nonlinear differentiator is proposed to work with the difficulties in deriving the explicit expression of system derivatives.Thereafter,a detailed stability analysis is conducted progressively on the angular control loop,reference trajectory observer loop,and the position control loop.A simulation scheme for a cluster of four rotorcraft UAVs tracking sinusoidal trajectory are presented and the formation control results are proven advantageous in comparison with the control protocol in previous literature.
