The problem of cooperative circular formation with limited target information for multiple Unmanned Aerial Vehicle (UAV) system is addressed in this paper. A pigeon-inspired circular formation control method is proposed to form the desired circular distribution in a plane based on the intelligent pigeon behavior during hovering. To reach the goal of prescribed radius and angular distribution, the controller is designed consisting of a circular movement part and a formation distribution part. Therein, the circular movement part is designed to make each UAV rotate around the specified circle at the same angular speed only using the relative position between the UAV and the target. The formation distribution part could adjust the angular distance between each UAV and its neighbors with the jointly connected network to reduce communication cost. To smooth the speed variation, nonlinear PID-type method is delivered throughout the evolution of the system. The convergence analysis of the proposed control protocol is presented using Lyapunov theory and graph tools. The effectiveness of the proposed control strategies is demonstrated through numerical simulations.

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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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