UAV swarm containment control inspired by spatial interaction mechanism of wolf-pack foraging

Zhang, DaiFeng; Duan, Haibin; Fan, YanMing

doi:10.1360/sst-2021-0042

Cited by 8 publications

(1 citation statement)

References 24 publications

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“…First, the UAV individual could acquire situation elements at the current time and space environment, fuse and analyze the information, and obtain the predictive inference of the states at the next moment to establish situation awareness. However, the actual battlefield environment faces challenges, such as incomplete information, the existence of interference, deception and attack signals [ 58 ]. Second, the decision-making process based on the environment cognition arranges the UAV swarm to execute the mission at a specific pattern depending on the dynamic task allocation and coordinated control mechanism [ 59 ].…”

Section: Unmanned Swarm Systemsmentioning

confidence: 99%

From animal collective behaviors to swarm robotic cooperation

Duan

Huo

Fan

2023

National Science Review

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The collective behaviors of animals, from schooling fish to packing wolves and flocking birds, display plenty of fascinating phenomena that result from simple interaction rules among individuals. The emergent intelligent properties of the animal collective behaviors, such as self-organization, robustness, adaptability, and expansibility, have inspired the design of autonomous unmanned swarm systems. This article reviews several typical natural collective behaviors, introduces the origin and connotation of swarm intelligence, gives the application case of animal collective behaviors. On this basis, the article focuses on the forefront of progress and bionic achievements of aerial, ground and marine robotics swarms, illustrating the mapping relationship from biological cooperative mechanisms to cooperative unmanned cluster systems. Finally, considering the significance of Coexisting-Cooperative-Cognitive (Tri-Co) human-machine system, the key technologies to be solved are given as the reference directions for the subsequent exploration.

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Section: Unmanned Swarm Systemsmentioning

confidence: 99%

From animal collective behaviors to swarm robotic cooperation

Duan

Huo

Fan

2023

National Science Review

Self Cite

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Distributed velocity-free formation tracking control for clustered UAVs under virtual leader-follower framework

Zhang,

Duan

2024

Sci. China Technol. Sci.

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Unmanned aerial vehicle formation control method based on improved artificial potential field and consensus

Wang,

Zhong,

Zhang

et al. 2024

IET Control Theory & Appl

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Formation coordination can improve the overall performance of unmanned aerial vehicle (UAV) systems, so it is important to realize coordinated formation control. To solve the problems of ineffective internal collision avoidance and communication distance maintenance in existing formation control methods, a UAV formation control algorithm based on an improved artificial potential field and consensus is proposed. First, an improved artificial potential field obstacle avoidance method is used to solve the problems of collision avoidance and communication distance maintenance within the formation by setting a communication risk zone and a collision risk zone and by defining the dynamic adjustment parameters of the inter‐UAV virtual force to improve the traditional artificial potential field method. Second, a time integrating factor is introduced, and an improved consensus‐based formation control method is employed to overcome the problem of the artificial potential field method falling into the local optimum easily. Simulation experiments were designed to analyse the trends of the UAV formation motion trajectory, inter‐UAV relative distance, attitude, and formation time. The analysis results show that the method can make the UAV formation consistent with the flight trajectory of the intended formation, solving the problems of collision avoidance and communication distance maintenance within the UAV formation.

show abstract

UAV swarm containment control inspired by spatial interaction mechanism of wolf-pack foraging

Cited by 8 publications

References 24 publications

From animal collective behaviors to swarm robotic cooperation

From animal collective behaviors to swarm robotic cooperation

Distributed velocity-free formation tracking control for clustered UAVs under virtual leader-follower framework

Unmanned aerial vehicle formation control method based on improved artificial potential field and consensus

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